Total 44 technical support engineer job vacancies in Pune

Role Overview

An AI Engineer at METRO unlocks the potential of AI for full organization. Rapidly delivers business-driven AI solutions by integrating existing cloud models and APIs, rather than inventing new algorithms. An AI Engineer builds digital agents and engineers the future of smart wholesale by delivering pragmatic, secure, maintainable, and observable AI powered solutions, that drive business value. Curious to get more information about the team, the products, or the tech stack?

Key Responsibilities

• Rapidly deliver business-driven AI solutions by integrating existing cloud models and APIs, focusing on practical implementation rather than developing new algorithms.
• Translate business goals into AI-powered solutions, ensuring technical feasibility through collaboration with squad leads, data scientists, architects, and full stack engineers.
• Integrate Google Cloud AI services and models into microservices and workflows to support scalable and maintainable solutions.
• Design, implement, deploy, and monitor intelligent agents to support automation and personalization.
• Build and maintain CI/CD pipelines using Cloud Build and GitHub Actions, collaborating closely with DevOps engineers and SREs for robust deployment and monitoring.
• Maintain comprehensive documentation including API references, runbooks, architecture diagrams, and conduct internal demos and training sessions.
• Ensure all AI solutions comply with METRO’s corporate policies on responsible AI and ethical standards.

SUMMARY:

You’ll join the Xplor Pay Development Team, which provides a full stack payment processing and acquiring platform to integrators, partners, and merchants. Whether small and independent or large franchises, we build services that customers can rely on. You will be involved in the entire software development lifecycle, working with Product Owners, Business Analysts, and others to help deliver and support required functionality across our payment platform, its user interfaces and APIs.

DUTIES AND RESPONSIBILITIES:

• Hands on problem-solving attitude with the ability to generate ideas/solutions and adapt and learn new technologies on the job.
• Write clean, testable, and well-documented code.
• Refactor existing code, write unit tests and review other teammates code.
• Fix problems and defects by collecting information, finding root causes, and implementing solutions.
• Conduct peer reviews for other members of the development team, ensuring that project conventions are adhered to and that requirements are correctly implemented.
• Participate in full-life cycle software development.
• Contribute to performance, diagnostic, and troubleshooting analysis of software.
• Create and maintain documentation for developed APIs.
• Involve and engage with other developers and other teams to motivate and connect with others.
• Mentoring junior team members and guiding them towards raising their own software quality standards.
• Estimate, plan and implement new features in collaboration with product and design.
• Code based on standards and best practices provided by your team lead.
• Keeping up to date with industry trends and technology developments.

Role Overview

An AI Engineer at METRO unlocks the potential of AI for full organization. Rapidly delivers business-driven AI solutions by integrating existing cloud models and APIs, rather than inventing new algorithms. An AI Engineer builds digital agents and engineers the future of smart wholesale by delivering pragmatic, secure, maintainable, and observable AI powered solutions, that drive business value. Curious to get more information about the team, the products, or the tech stack?

Key Responsibilities

• Rapidly deliver business-driven AI solutions by integrating existing cloud models and APIs, focusing on practical implementation rather than developing new algorithms.
• Translate business goals into AI-powered solutions, ensuring technical feasibility through collaboration with squad leads, data scientists, architects, and full stack engineers.
• Integrate Google Cloud AI services and models into microservices and workflows to support scalable and maintainable solutions.
• Design, implement, deploy, and monitor intelligent agents to support automation and personalization.
• Build and maintain CI/CD pipelines using Cloud Build and GitHub Actions, collaborating closely with DevOps engineers and SREs for robust deployment and monitoring.
• Maintain comprehensive documentation including API references, runbooks, architecture diagrams, and conduct internal demos and training sessions.
• Ensure all AI solutions comply with METRO’s corporate policies on responsible AI and ethical standards.

Quadric delivers its GPNPU as soft IP — RTL and implementation collateral — enabling customers to integrate our processor into their own SoCs across a range of process nodes and foundries. You will drive PPA optimization across IP configurations, build the scalable reference flows customers use to evaluate and integrate our IP, and provide hands-on implementation support to customers working toward their tapeouts.

Responsibilities

PPA Optimization & Analysis

• Drive PPA analysis and optimization for Quadric GPNPU soft IP across process nodes and hardware configurations — timing, area, leakage, and dynamic power
• Apply low-power techniques (clock gating, multi-Vt, operand isolation) and synthesis/P&R knobs to hit frequency and area targets
• Characterize the IP design space across configurations and build PPA models that support customer evaluations and pre-sales engagements
• Partner with RTL and architecture teams early to quantify tradeoffs and influence design decisions before they become costly to reverse

Reference Flow Development

• Build and maintain a scalable RTL-to-GDS reference flow for Quadric soft IP that customers can use to evaluate, integrate, and close PPA in their own SoC environment
• Ensure the flow is portable across supported process nodes with clear BKMs, SDC templates, floorplan scripts, and integration guidelines
• Develop TCL and Python automation — and leverage AI coding tools such as Claude — to accelerate flow development, reduce manual effort, and improve repeatability
• Qualify EDA tool updates and benchmark QoR impact before rolling into the reference flow

Customer Integration & Tapeout Support

• Act as the primary PD contact for customers integrating Quadric soft IP, guiding them from evaluation through their SoC tapeout
• Help customers adapt the reference flow to their process node, foundry PDK, and internal design environment
• Triage and resolve customer-reported implementation issues — timing, congestion, power, or flow failures — working with internal teams to deliver fixes or updated collateral
• Support FAE and business development with PPA feasibility studies for new customer engagements

Collaboration & Documentation

• Work with architecture, RTL, and software teams to ensure IP deliverables meet customer-facing PPA targets
• Document methodologies, BKMs, and optimization learnings; maintain process node bring-up guidelines to support IP portability

Education & Experience

• BS/MS in Electrical Engineering, Computer Engineering, or related field
• 4+ years of ASIC or processor IP physical design experience focused on PPA optimization and flow development across advanced nodes

Technical Skills

• Proficiency with industry-standard physical design tools from Synopsys or Cadence (synthesis, place-and-route, and timing analysis)
• Experience with advanced FinFET process nodes (16nm and below); multi-node experience preferred
• Strong TCL scripting and Python automation skills
• Solid understanding of synthesis and P&R levers for PPA — timing paths, cell selection, congestion, and power intent
• Hands-on experience with low-power design techniques and MCMM timing analysis
• Comfort using AI tools (e.g., Claude, Copilot) to accelerate script development, automate repetitive EDA tasks, and improve workflow productivity
• Understanding of DFT concepts (scan, ICG bypass) and their physical design implications

Nice to Have

• Experience delivering soft IP to external customers or supporting SoC integrators through tapeout
• Background in AI accelerator, NPU, or DSP processor IP implementation
• Exposure to metrics-driven QoR tracking and large-scale synthesis run management

About Job:

Senior Software Development Engineer, Pune, India 

 Responsibilities:

• Understanding business requirements and how they fit into the overall, global solution design  
• Embracing end-to-end the development and maintenance of any new feature including the estimation, the development and validation of new code, the design of testing scenarios up to the deployment into production  
• Following source and test-driven development best practices  
• Troubleshooting and identifying root cause analysis while resolving the issues  

Technical Lead — Python | GoLang| aiohttp | REST |Pandas

At Assent, we’re solving complex technical challenges with global impact. Our multi-tenant SaaS platform helps the world’s most influential companies gain deep visibility into their supply chains—enabling them to manage risk, ensure compliance, and take real action on issues like forced labor, environmental sustainability, and ethical sourcing.

We’re looking for a Technical BE Lead with deep expertise in Python or GoLang and Back-end architecture to own the design system strategy and lead the evolution of our product [expanded scope and leadership]. You should have a basic understanding of Angular and UI Technologies. You’ll work closely with engineering leaders, product managers, and architects to define technical direction, enforce architectural standards, and ensure delivery of scalable, accessible, and well-tested WebApp solutions across multiple teams.

You’ll operate in a high-trust CI/CD environment—every commit goes to production, and there’s no separate QA team. That means you’ll be responsible for setting expectations and ensuring quality practices are embedded in the development process. You’ll drive the creation of automated test coverage strategies, web app development and documentation.

We work with the latest technology and plan to keep doing so. Our team uses tools like GitHub Copilot to help with AI-powered coding, Lucid for architectural design, and we’re always open to trying new tools that can help us create better experiences for our customers. 

Our Product Tech Stack will Includes:

• C#, Python
• Pandas
• PyTest
• Boto3
• NumPy/SciPy
• AIOHTTP
• CI/CD pipelines that support rapid, high-quality delivery to production
• Angular

We value system thinking, performance, and platform maintainability. You’ll help ensure that UI decisions support both short-term product goals and long-term architectural integrity.

What You’ll Do:

As the Python Tech Lead for this foundational pilot, you will play a pivotal role in designing and implementing the core serverless backend architecture that powers the user interaction and data processing pipeline. Your focus will be on building a scalable, observable, and maintainable API and orchestration layer leveraging AWS services. Key responsibilities include:

• Design and develop RESTful APIs using AWS API Gateway integrated directly with Lambda functions, removing the need for a traditional monolithic BFF.
• Implement endpoint logic in Python-based Lambda functions, focusing on modular, single-responsibility functions such as file upload, status checks, and analytics retrieval.
• Ensure the API layer abstracts away all backend complexity from the Angular frontend, providing clean and reliable interfaces to support user interactions.
• Support core user flows, such as uploading CMRT files and retrieving analytic results, by implementing and exposing APIs that connect to appropriate backend services.
• Partner closely with frontend engineers, data platform teams, and Gold-tier data engineers to define requirements, ensure backend compatibility, and surface data insights effectively.
• Work with data engineers to integrate the API layer with the medallion architecture (Bronze, Silver, Gold), routing requests dynamically based on the data and analytics context.
• Implement and maintain AWS Step Functions workflows to orchestrate file processing, from ingestion through to entity resolution and persistence.
• Use EventBridge to trigger workflows on CMRT file uploads to S3, ensuring the system is extensible for future ingestion paths (e.g., SFTP, email, or 3rd-party systems).
• Design and implement a robust automated unit testing strategy across all Lambda functions using tools such as pytest, moto, and unittest.mock.
• Establish and enforce test coverage thresholds and integrate testing into the CI/CD pipeline.
• Set coding standards, enforce clean architecture principles, and mentor other developers working on the Lambda and orchestration components.

By leading the development of this cloud-native, event-driven architecture, you'll enable rapid iteration, scalability, and future extensibility of the RM Foundational Pilot platform.

We are looking for a hands-on Technical Lead (IC role) who can drive technical excellence, mentor teams, and
contribute to building scalable, high-performing applications. This role is ideal for someone passionate about
full-stack development and modern technologies, with strong leadership and problem-solving skills.

Key responsibilities include:
▸ Lead technical design and development for complex projects.
▸ Collaborate with architects and product managers to define technical roadmaps.
▸ Stay hands-on with coding, code reviews, and troubleshooting critical issues.
▸ Mentor and guide team members on best practices and emerging technologies.
▸ Ensure high-quality deliverables through robust architecture and clean code.
▸ Drive adoption of modern development practices, CI/CD, and cloud solutions.

Reporting to the Manager of Product Technical Support Tier 1, you will be the first point of contact for Assent Compliance’s midmarket customers and suppliers. You’ll handle inbound and outbound support inquiries via calls, webforms, emails, live chat, and screen-share sessions. As a Tier 1 Technical Analyst, you will play an integral role in ensuring customer success by providing timely, high-quality support and maintaining detailed documentation in a regulatory compliance environment. This position emphasizes both adherence to established processes and the creative problem-solving skills necessary to resolve unique or complex user issues.

KEY REQUIREMENTS AND RESPONSIBILITIES 

• Serve as a first responder to support requests, managing cases from initial contact to resolution

• Engage with clients and suppliers in a professional, friendly manner to enhance the customer experience

• Use troubleshooting tools, basic SQL queries, and AI-driven insights to identify root causes of issues

• Document all interactions, steps, and resolutions thoroughly for consistent case management

• Resolve routine to moderately complex issues using established processes and creativity for unique problems

• Escalate complex product defects or high-impact cases to Tier 2

• Contribute to multi-channel support by providing assistance through email, phone, chat, and screen-share

• Adhere to set performance metrics (e.g., first response time under 2 hours, quality rating ≥95%)

• Participate in training and knowledge-sharing sessions to stay updated on new features and best practices

• Collaborate with peers and higher-tier teams in “swarm” sessions to resolve challenging issues

• Manage your queue efficiently, consistently updating cases with progress and new information

• Work various shifts (including evenings and weekends) to support a global 24/7 operation

• Follow corporate security policies and handle data in accordance with regulatory requirements

This is not an exhaustive list of duties. Responsibilities may be altered and/or added from time to time to meet business needs. 

Sales of all Bosch Rexroth products for Agriculture segment in WZ
Regular customer visits & building excellent customer relationship
Generating new enquiries
Techno-commercial proposal offering & negotiation with customers
Driving new projects
Offer new concepts & products to grow market share
Responsible for creating excellent customer experience
Responsible for achieving all key KPI’s
Resolving customer quality topics on top priority

About Job:

AI Platform & Agentic Systems Engineer (AI / ML), Pune, India (Hybrid)

Experience- 5+ years 

We are looking for a high-impact AI Platform & Agentic Systems Engineer who will help drive the AI transformation across our organization.

This role goes beyond traditional machine learning development. The engineer will design and build AI-powered platforms, intelligent agents, orchestration layers, and enterprise AI workflows that enhance productivity, automate processes, and unlock intelligence across systems and data.

You will work extensively with LLMs, SLMs, agentic AI architectures, vector databases, RAG pipelines, orchestration frameworks, and enterprise integrations to build scalable AI-enabled solutions.

The ideal candidate is someone who actively builds with AI, understands modern AI ecosystems deeply, and can convert AI capabilities into real-world production systems.

Key Responsibilities

Enterprise AI Platform Development

• Build and maintain internal AI platforms and services that enable teams across the organization to leverage AI capabilities

• Develop reusable AI APIs, SDKs, and microservices for enterprise adoption

• Integrate AI capabilities into existing systems, developer workflows, and business platforms

• Enable organization-wide adoption of AI-assisted workflows and automation

Agentic AI & Autonomous Systems

• Design and implement agent-based architectures capable of multi-step reasoning and task execution

• Build autonomous AI agents that interact with APIs, enterprise tools, and data systems

• Develop multi-agent systems capable of collaboration and workflow orchestration

• Implement tool-using agents that can dynamically select and use enterprise services

Examples may include:

• AI engineering assistants
• workflow automation agents
• data intelligence agents
• internal knowledge agents

AI Orchestration & Workflow Engines

• Design AI orchestration layers that coordinate models, tools, and workflows

• Build pipelines that manage:

o multi-step reasoning

o task decomposition

o tool execution

o memory and context management

• Work with orchestration frameworks such as:

o LangChain

o LlamaIndex

o CrewAI

o similar orchestration frameworks

• Enable structured interaction between LLMs, enterprise tools, APIs, and knowledge systems

LLM / SLM Systems

• Work with modern Large Language Models (LLMs) and Small Language Models (SLMs)

• Evaluate and select models based on:

o performance

o latency

o cost

o reliability

• Implement advanced techniques such as:

o prompt engineering

o prompt chaining

o context window management

o function calling

o tool invocation

Retrieval-Augmented Generation (RAG)

• Design and implement RAG architectures for enterprise knowledge retrieval

• Build pipelines that integrate LLMs with internal knowledge bases

• Optimize retrieval systems to improve contextual accuracy and response relevance

• Implement indexing pipelines and semantic retrieval strategies

Vector Databases & Knowledge Infrastructure

• Work with vector databases and embedding systems to enable semantic search

• Implement knowledge indexing pipelines using:

o Pinecone

o Weaviate

o Milvus

o Chroma

• Build scalable knowledge retrieval layers for AI applications

Machine Learning & AI Model Development

• Build ML pipelines using Python-based machine learning stacks

• Work with ML frameworks including:

o PyTorch

o TensorFlow

o Scikit-learn

o Hugging Face ecosystem

• Develop data pipelines, feature engineering workflows, and model training pipelines

• Evaluate model performance and experiment with different architectures

AI Infrastructure & Model Deployment

• Deploy AI workloads in cloud and containerized environments

• Build model inference pipelines and scalable AI services

• Work with infrastructure tools such as:

o Docker

o Kubernetes

o cloud AI platforms

• Implement monitoring, evaluation, and lifecycle management for AI systems

AI Development Environment & Tooling

• Work within AI-enabled development environments

• Leverage modern AI tooling including:

o VS Code AI ecosystem

o Copilot

o AI coding assistants

• Build internal tools that improve AI productivity across engineering teams

AI Safety, Guardrails & Evaluation

• Implement mechanisms to ensure safe and reliable AI outputs

• Build guardrails to reduce hallucinations and unsafe responses

• Develop AI evaluation frameworks and benchmarks

• Monitor AI system performance and continuously improve reliability

THE POSITION:

We are looking for a Senior Technical QA Engineer with strong expertise in test automation using Python to deliver high-quality, scalable, and reliable software solutions. This role will play a key part in building robust automation frameworks, improving QA processes, and ensuring seamless product delivery in an agile environment.

ESSENTIAL DUTIES AND RESPONSIBILITIES:

Our employees are tasked with delivering excellent business results through the efforts of their teams.  These results are achieved by:

• Design, develop, and execute test strategies, test plans, and test cases for complex applications
• Build and maintain automation frameworks using Python
• Develop and execute automated test scripts for UI, API, and backend systems
• Collaborate with developers, product owners, and business analysts to ensure quality across the SDLC
• Perform functional, regression, integration, and API testing
• Identify, track, and resolve defects using tools like JIRA
• Integrate automated tests into CI/CD pipelines to enable continuous testing
• Drive improvements in QA processes, tools, and automation coverage
• Mentor junior QA engineers and promote best practices

Role Overview

- A senior full stack engineer with strong experience in MuleSoft integration and API-led connectivity.
- Someone with a solid foundation in Java and backend development, and hands-on experience with MuleSoft Anypoint Platform.
- A certified MuleSoft professional who can design, build, and manage APIs and integrations in a distributed, cloud-native environment.

Key Responsibilities

• Design, develop, and maintain MuleSoft Flows and integrations using Anypoint Studio and related tools.
• Build and maintain services using Java and Spring Boot.
• Lead the modernization of integration architecture and contribute to microservices design.
• Work closely with architects and product managers to align on integration strategies.
• Ensure performance, scalability, and security of integration solutions.
• Promote best practices in API design, testing, and CI/CD automation.
• Collaborate with DevOps teams for cloud-native deployments (e.g., Kubernetes, GCP).

Join our DevOps Engineering team as a Senior Database Engineer to design, build, and engineer cloud-native database platforms across a modern, multi-engine data stack. This is an engineering role, not a DBA role, focused on building scalable systems, writing infrastructure-as-code, and embedding databases into software delivery pipelines.

You'll work closely with DevOps and Product Engineering to build high-performing data infrastructure that supports critical applications and analytics.  You will own and evolve a diverse ecosystem spanning AWS RDS, Aurora, DynamoDB, Redshift, Azure SQL, PostgreSQL, Snowflake, and NoSQL engines, integrating AI-driven automation and MLOps-ready data foundations to support critical applications and machine learning workflows.

Key Responsibilities

Multi-Engine Cloud Data Architecture & Platform Engineering

• Design, build, and engineer hybrid data solutions spanning relational (PostgreSQL, Aurora, RDS, Azure SQL), columnar (Redshift, Snowflake), and NoSQL (DynamoDB, DocumentDB, OpenSearch) engines — selecting the right engine per workload.
• Architect cloud-native data lakehouse platforms on AWS using S3, Lake Formation, Glue, and open formats (Apache Iceberg, Delta Lake, Parquet), with Azure Data Lake as a secondary target.
• Implement and manage Medallion Architecture (Bronze / Silver / Gold) patterns to support raw ingestion, curated analytics, and business-ready datasets.
• Build and optimize hybrid data platforms spanning operational databases (PostgreSQL / RDS / Aurora / DynamoDB) and analytical systems (Snowflake / Redshift).
• Develop and maintain semantic layers and analytics models to enable consistent, reusable metrics across BI, analytics, and AI use cases.
• Engineer efficient data models, ETL/ELT pipelines, and query performance tuning for analytical and transactional workloads.
• Engineer replication topologies, partitioning strategies, and data lifecycle automation as code — not manual DBA operations.
• Build automated schema migration pipelines (Flyway/Liquibase) and data versioning workflows integrated into CI/CD replacing manual schema change management.
• Design and implement API-first data access patterns, enabling engineering teams to interact with databases through well-defined, versioned interfaces rather than direct connection strings.

Advanced Data Pipelines, Streaming & Orchestration

• Engineer ELT/ETL pipelines using AWS-native services (Glue, Kinesis, MSK, Step Functions, EventBridge) and modern tooling (dbt, Airflow) for batch, micro-batch, and near-real-time workloads.
• Build streaming data pipelines using AWS Kinesis Data Streams, Kinesis Firehose, and MSK (Managed Kafka) for event-driven, low-latency ingestion across multiple database targets.
• Implement data quality checks, schema enforcement, lineage, and observability across pipelines.
• Optimize performance, cost, and scalability across ingestion, transformation, and consumption layers.
• Implement change data capture (CDC) using AWS DMS, Debezium, or native engine features to synchronize data across SQL, NoSQL, and analytical systems.

NoSQL & Document Store Engineering

• Design and optimize DynamoDB schemas using single-table design patterns, GSIs, LSIs, and DynamoDB Streams for event-driven architectures.
• Architect DocumentDB (MongoDB-compatible) clusters for document workloads requiring flexible schema and hierarchical data models.
• Build and manage OpenSearch / ElasticSearch clusters for full-text search, log analytics, and observability use cases.
• Evaluate and recommend the right NoSQL engine (DynamoDB vs DocumentDB vs OpenSearch vs ElastiCache) based on access patterns, latency, and cost profile.
• Implement TTL policies, DynamoDB Accelerator (DAX), and ElastiCache (Redis/Memcached) for high-throughput caching layers.

AI-Enabled Data Engineering & MLOps Foundations

• Apply AI and ML techniques to data architecture and operations, including intelligent data quality validation, anomaly detection, schema drift detection, and query workload pattern analysis — using AWS SageMaker and Amazon Bedrock.
• Design and build ML-ready data foundations: SageMaker Feature Store, training dataset pipelines, experiment tracking, and inference data pipelines using AWS-native MLOps services.
• Integrate LLM capabilities via Amazon Bedrock for AI-assisted data documentation, query generation, lineage summarization, and automated data cataloging.
• Implement vector database solutions (pgvector on Aurora/RDS, OpenSearch k-NN) to support AI similarity search and retrieval-augmented generation (RAG) use cases.
• Build AI-powered observability using ML-driven anomaly detection on pipeline metrics, query performance trends, and data quality SLAs.

Software Engineering, DevOps & Infrastructure as Code

• Build and manage all data infrastructure as code using Terraform and AWS CDK — covering RDS, Aurora, DynamoDB, Redshift, Glue, MSK, Kinesis, Snowflake, and supporting IAM/networking components.
• Integrate database changes into CI/CD pipelines (GitHub Actions, AWS CodePipeline) with automated schema testing, data contract validation, deployment, and rollback.
• Develop internal platform tooling using Python, SQL, and AWS SDK (boto3) — building self-service capabilities that allow engineers to provision governed database environments on demand.
• Implement database-as-code practices: automated schema migrations, snapshot/restore testing pipelines, and environment clone automation — eliminating manual DBA provisioning tasks.
• Build and publish internal data platform APIs and SDKs that abstract database complexity from application teams.

Security, Governance & Compliance Engineering

• Engineer enterprise-grade data governance across all engines: RBAC, column/row-level security, field-level encryption, dynamic data masking, and comprehensive audit logging, implemented as code, not manual configuration.
• Define and enforce data contracts and ownership using AWS Lake Formation, Glue Data Catalog, and Snowflake governance — versioned and managed in source control.
• Partner with Security and Compliance teams to ensure audit readiness and regulatory alignment (SOC 2, HIPAA, GDPR where applicable).
• Manage AWS IAM policies, KMS encryption, VPC security groups, and private endpoints (PrivateLink, VPC Endpoints) for least-privilege access and network isolation.
• Implement secrets management using AWS Secrets Manager and Parameter Store with automated credential rotation for all database engines.

The Principal Design Engineer, Port Solutions Electrics, will be responsible for creating high‑quality electrical designs and documentation for port cranes or industrial cranes. The role involves interpreting project specifications, preparing detailed engineering drawings, ensuring compliance with international standards, and coordinating with project teams to deliver accurate and timely outputs.

Key Responsibilities

• Study and interpret project specifications, technical requirements, and engineering inputs.
• Prepare panel layouts, single line diagrams (SLDs), schematics, Bill of Materials (BOM), and cable lists as per project requirements.
• Plan and manage personal work activities to meet project timelines with high-quality deliverables.
• Improve and maintain the quality of drawings as per customer and company standards.
• Ensure effective communication and coordination within the team.
• Adhere to company policies, processes, and engineering guidelines.
• Travel to international customer sites as required (valid passport mandatory).
• Follow and maintain awareness of ISO 14001 & ISO 45001 standards.

The role is based in our office in SP Infocity, Pune – but it goes without saying that the remote & hybrid working is a part of our modern ways of working.

Required Qualifications & Skills

Educational Qualification

• Bachelor's degree in Electrical / Electronics / Mechatronics Engineering from a reputed university.

Experience

• Minimum 4–6 years of electrical design experience in port cranes or industrial cranes.

Technical Skills

• Strong knowledge of electrical engineering fundamentals:
  • Power distribution
  • Motor control (AC/DC drives)
  • Control and protection circuits
• Expertise in Zuken E3 and Teamcenter / SAP.
• Proficiency in creating electrical drawings including panel layouts, SLDs, schematics, BOMs, and cable lists.
• Experience in cable selection, LV switchgear selection, and understanding of motor control and protection circuits.
• Hands-on experience with AutoCAD (preferred).
• Familiarity with standards: IEC / UL / EN / CSA applicable to crane systems.
• Experience in port cranes or industrial cranes is an added advantage.

Soft Skills

• Good communication skills in English.
• Strong teamwork and collaboration abilities.
• Ability to work independently with attention to detail.

We are looking for…

A mid-level full stack engineer with expertise in both frontend and backend technologies.
In this role, you will be part of a six people team working on METRO’s global solution for calculating and invoicing bonus payments from suppliers which is used in a standardized way across all METRO countries. This solution is built upon a large-scale codebase including legacy code in Oracle PL/SQL that integrates backend services and a complex React frontend. Your contribution will be pivotal in modernizing the solution and facilitating the split into modular, scalable components while ensuring reliability and design consistency.

Key Responsibilities

• Design, develop, and maintain both frontend (React, Redux, Material UI) and backend (Java, Spring Boot) components.
• Support the modernization and modularization of a large monolithic frontend & backend codebase.
• Collaborate with architects and service managers as well as business and solution experts to align on long-term technical strategies and system design.
• Ensure system performance, security, and scalability across frontend and backend layers.
• Promote clean code practices, automated testing, and CI/CD pipelines to maintain development excellence.
• Work closely with DevOps and platform teams to ensure cloud-native deployments on GCP with Kubernetes and Istio.