Total 4 software engineer job vacancies

We are looking for an Engineering Manager / Lead Software Engineer to take on complex and meaningful technical challenges in the public sector, driving digital transformation that directly improves lives at scale.

In this role, you will be responsible for setting technical direction, shaping engineering processes, and ensuring delivery of one or more products owned by your team. You will also play a key role in building an engineering culture that values excellence, collaboration, and long-term impact.

Job Responsibilities:

• Defining your team’s engineering vision, strategy, and roadmap in alignment with broader organizational goals.
• Staying on top of industry trends, with strong knowledge of how systems should be architected, engineered, and maintained at scale.
• Designing and guiding the implementation of systems across SaaS solutions, leveraging cloud technologies where appropriate.
• Partnering with stakeholders to prioritize and manage product roadmaps, ensuring incremental and effective delivery towards long-term vision.
• Creating and maintaining a technical plan that anticipates future product and infrastructure needs.
• Coaching and mentoring engineers through regular feedback, supporting professional growth and career development.
• Driving adoption of best practices in quality, reliability, performance, and security within your teams.
• Encouraging strong engineering culture and introducing tools/processes that maximize effectiveness and impact.
• Actively identifying and initiating high-value engineering initiatives that contribute to the public good.
• Contributing to recruitment, particularly for senior technical roles.

Job Requirements:

• Proven experience building and operating large, high-availability software systems at scale.
• At least 10 years of development experience, with 5+ years coaching and mentoring engineering teams of 5+ people.
• Experience with modern full-stack application development, spanning contemporary front-end frameworks and scalable backend services across multiple programming languages.
• Hands-on technical expertise across the technology stack, including infrastructure, client-side, backend services, APIs, databases, performance, and data.
• Strong background in end-to-end system development, from user interfaces through backend and integration layers.
• Familiarity with Agile development, modular design, automation, TDD, CI/CD pipelines, pair programming, and infrastructure automation.
• Exposure to cloud platforms (e.g. AWS, Azure) and container technologies (e.g. Docker, Kubernetes).
• Excellent understanding of engineering leadership, balancing technical expertise with the soft skills needed to inspire and guide teams.
• Passion for engineering craftsmanship, teamwork, and creating meaningful impact through technology.
• Strong ability to lead teams toward achieving ambitious goals together.

About the Role
We are looking for a Junior to Mid-Level ML Engineer to join the Model Engineering team. This role is suited for someone who enjoys working hands-on with computer vision models and understands models as systems to be trained, evaluated, improved, and optimised. You will work across the model lifecycle, including dataset preparation, architecture development, model training, evaluation, performance analysis, and optimisation for real-world computer vision applications.

Responsibilities

• Train, fine-tune, and evaluate computer vision models for classification, object detection, segmentation, pose estimation, and action recognition.
• Improve model performance through architecture enhancements, custom heads, backbone modifications, loss functions, and training strategy optimisation.
• Design experiments, conduct ablation studies, benchmark new techniques, and analyse model trade-offs.
• Investigate edge cases, debug failure cases, and improve model accuracy, robustness, and efficiency.
• Optimise models based on practical constraints such as latency, throughput, resource usage, and hardware limitations.
• Collaborate with engineering teams to improve dataset quality, model performance, and system reliability.

Requirements

• Bachelor’s degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or a related technical field.
• At least 2 years of hands-on experience training, fine-tuning, and evaluating computer vision models.
• Strong hands-on experience with PyTorch and/or TensorFlow.
• Proficiency in Python and familiarity with Linux environments and command-line tools.
• Experience with computer vision tasks such as classification, object detection, segmentation, pose estimation, or action recognition.
• Experience modifying models beyond configuration-level changes, including architectures, backbones, heads, loss functions, or training pipelines.
• Experience designing experiments, conducting ablation studies, analysing model performance, and debugging failure cases.
• Familiarity with multimodal, vision-language, foundation, or open-vocabulary models.
• Experience with model optimisation techniques such as quantisation, pruning, or distillation.
• Familiarity with experiment tracking, reproducibility, and structured machine learning workflows.

Our client is a fast-growing AI company building enterprise-grade agentic automation solutions for large organizations. They are looking for a hands-on, client-facing AI engineer to work directly with enterprise clients and bring AI-driven automation workflows into production.

This role is best suited for a strong engineer who enjoys solving ambiguous customer problems, working close to real business operations, and moving from discovery to implementation quickly. You will help clients identify where AI agents can create practical impact, then design, build, integrate, deploy, and iterate solutions within complex enterprise environments.

You will work across backend engineering, solution design, integrations, data flows, deployment, and customer engagement, with a strong focus on reliability, business value, and production outcomes.

Key Responsibilities

• Partner directly with enterprise customers to understand their workflows, pain points, technical environments, and success criteria.
• Translate ambiguous business problems into clear technical plans, solution designs, and production-ready implementations.
• Build, configure, and deploy AI agents and automation workflows that connect with customer systems, data sources, APIs, and business processes.
• Own the delivery lifecycle from discovery and scoping through build, testing, launch, monitoring, and ongoing iteration.
• Write high-quality code for backend logic, integrations, workflow automation, data handling, and deployment requirements.
• Work with real customer data and production environments to test performance, measure outcomes, and improve solution effectiveness.
• Collaborate with product and engineering teams to improve the platform based on customer needs, deployment learnings, and field feedback.
• Run technical workshops, guide customers through implementation decisions, and explain technical trade-offs clearly to both technical and non-technical stakeholders.
• Identify repeatable patterns, create documentation, improve internal tools, and help scale delivery practices as the team grows.
• Take ownership of reliability, performance, maintainability, and long-term customer success after deployment.

Requirements

• Minimum 6 years of experience in software engineering, AI engineering, implementation engineering, technical consulting, or similar hands-on technical roles.
• Strong backend engineering fundamentals, including system design, APIs, integrations, data flows, and production systems.
• Experience with AI agents, LLM applications, automation platforms, workflow tools, or data-heavy enterprise systems.
• Experience building or deploying AI solutions in complex customer environments, especially where requirements are ambiguous or evolving.
• Comfort working directly with enterprise customers, including business, operations, IT, and technical stakeholders.
• Ability to quickly understand customer workflows and identify where automation or AI can deliver practical business impact.
• Strong ownership mindset, with the ability to create clarity, drive decisions, and move projects forward independently.
• Clear communication skills, with the ability to explain technical concepts, implementation plans, risks, and trade-offs in a practical way.
• Experience working with production systems, including testing, debugging, monitoring, performance improvement, and ongoing iteration.
• Regular use of AI tools and a practical understanding of what current AI technologies can and cannot do.
• Comfort operating in a fast-moving, early-stage environment where priorities may shift and solutions need to be developed quickly but thoughtfully.

Nice to have

• Experience in enterprise implementation, deployment, professional services, customer engineering, or technical consulting.
• Experience working with large enterprise clients in Singapore, especially across FSI, telco, insurance, aviation, or other complex industries.
• Startup or zero-to-one environment experience.

Dear Applicant,

If you or someone you know isinterested, please send the CV directly to VeronicaE@evolutionjobs.sg (mostpreferred, as I may overlook some CVs due to the high volume).

Please note that visasponsorship is not available at this time.

JD

AI Solutions Engineer – 1-Year Renewable Contract
Industry: Insurance
Location: Singapore
Contract: 1-year renewable

We are looking for an AI Solutions Engineer tosupport AI/GenAI initiatives within the insurance domain. The ideal candidateshould have strong hands-on experience in AWS / Azure, with the abilityto design, build, and deploy AI solutions in an enterprise environment.

Key Responsibilities:

Design, develop, and implement AI/GenAI solutions using Amazonand Microsoft.

Work with business and technology stakeholders to understandrequirements and translate them into scalable AI solutions.

Build and integrate AI models, APIs, workflows, andautomation tools into existing systems.

Support proof-of-concepts, solution design, testing,deployment, and production readiness.

Collaborate with data, cloud, security, and applicationteams to ensure solutions meet enterprise standards.

Provide technical guidance on AI architecture, cloudintegration, and best practices.

Requirements:

Strong experience as an AI Engineer / AI SolutionsEngineer / Cloud AI Engineer / Machine Learning Engineer.

Must have hands-on experience with AWS/Azure

Good understanding of GenAI, LLMs, prompt engineering, RAG,model integration, and AI solution deployment.

Experience with Python, APIs, cloud-native architecture, andenterprise application integration.

Insurance or financial services experience is highlypreferred.

Strong communication skills and ability to work with bothtechnical and business stakeholders.