Total 2 Others level Information Technology job vacancies in Mumbai

Job Description: Prompt Engineer

About the Role

We are looking for a highly creative and analytical Prompt Engineer to join our team. You will design, test, and optimize prompts for large language models (LLMs) to improve accuracy, efficiency, and usability of AI-driven applications. The role requires a mix of technical knowledge, problem-solving skills, and domain understanding to bridge human intent with AI capabilities.

Key Responsibilities

• Design, develop, and refine prompts for AI/LLM applications to ensure high-quality and contextually accurate outputs.
• Collaborate with product, engineering, and data teams to integrate prompt strategies into applications and workflows.
• Conduct A/B testing and evaluate prompt effectiveness across different scenarios.
• Maintain a knowledge base of reusable prompt templates and frameworks.
• Stay updated with advancements in generative AI, Agentic AI, prompt engineering techniques, and tooling
• Analyze outputs, debug issues, and propose prompt modifications for continuous improvement

Required Skills & Qualifications

• Strong understanding of large language models (LLMs) such as GPT, Claude, LLaMA, or similar.n
• Understanding of Agentic frameworks specifically of LangChain, LangGraph
• Experience with prompt design, chaining, and optimization.
• Proficiency in at least one programming language (Python preferred).
• Strong analytical and problem-solving skills.
• Excellent written and verbal communication skills.
• Ability to work in cross-functional teams and translate business needs into AI solutions.

Overview

As an AI Technical Lead / Architect focused on Generative and Agentic AI, you will architect, design, and lead the delivery of production-ready, enterprise-grade AI systems. You will take ideas from early experimentation and prototypes through scalable, secure, and reliable AI solutions used by real customers and internal users.

The role focuses on building intelligent, agent-based systems that can reason, plan, integrate with tools, and make autonomous decisions at enterprise scale.

Strong engineering mindset with end-to-end ownership, experience delivering real-world AI solutions at enterprise scale, and ability to mentor and influence across teams.

Key Responsibilities

Technical Leadership & Architecture

• Provide technical leadership and architecture for Generative and Agentic AI initiatives
•  Design end-to-end AI system architectures covering orchestration, data, APIs, security, and deployment
• Build LLM-based solutions using RAG, embeddings, prompt engineering, function calling, and agentic workflows
• Ensure production readiness including CI/CD, testing, observability, scalability, security, and cost optimization
• Mentor AI engineers and collaborate with business and technology stakeholders

Generative & Agentic AI Engineering

• Design and build LLM-based systems using techniques such as:
•  Retrieval Augmented Generation (RAG)
•  Embeddings and vector search
• Prompt engineering and prompt optimization
• Function calling and tool usage
• Agentic and multi-agent workflows
• Build AI systems that integrate LLMs with APIs, data platforms, enterprise applications, and workflow engines
• Apply modern AI evaluation approaches including automated testing, benchmarking, and qualitative + quantitative LLM evaluation

Engineering Exc ellence & Operations

• · Apply strong software engineering and distributed systems principles to AI development
• · Design for observability, including logging, metrics, tracing, alerts, and model performance monitoring
• · Diagnose and resolve production issues related to latency, reliability, data quality, and model behavior
• · Balance innovation speed with operational excellence and long-term maintainability

Collaboration, Enablement & Mentorship

• · Work closely with business stakeholders to translate real-world problems into AI-driven solutions
• · Partner with AI engineers, data scientists, and platform teams to scale delivery
• · Mentor and coach engineers on Generative AI, Agentic AI, and cloud-native best practices
• · Support low-code and Copilot/Flow-style solutions where appropriate, while ensuring architectural integrity