Artificial Intelligence Engineer

Job Title: AI Engineer

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At ValueMomentum’ s Technology Solution Centre, we are a team of passionate engineers who thrive on tackling complex business challenges with innovative solutions while transforming the P&C insurance value chain. We achieve this through strong engineering foundation and continuously refining our processes, methodologies, tools, agile delivery teams, and core engineering archetypes. Our core expertise lies in six key areas: Cloud Engineering, Application Engineering, Data Engineering, Core Engineering, Quality Engineering, and Domain expertise.

Join a team that invests in your growth. Our Infinity Program empowers you to build your career with role-specific skill development leveraging immersive learning platforms. You'll have the opportunity to showcase your talents by contributing to impactful projects.

Role Summary

As an AI Engineer, you will be responsible for building full-stack generative and agentic AI solutions—spanning from prompt logic and orchestration to APIs, UIs, and infrastructure integration. You will work in a cross-functional delivery pod to implement scalable, reusable components and rapidly transition PoCs into production-ready systems.

This role requires hands-on fluency across GenAI tools, LLM frameworks, and integration patterns, with the ability to balance experimentation with disciplined engineering practices.

Key Responsibilities

· Build agentic workflows using orchestration frameworks (e.g., LangGraph, custom DAGs, FSMs)

· Develop modular components: prompt chains, retrieval functions, tool integrations, fallback logic

· Implement containerized APIs and UI interfaces to surface AI capabilities in client-facing systems

· Collaborate with Solutions Architect to translate business use cases into working systems

· Participate in prompt iteration, eval loop integration, and context memory design

· Work alongside Platform & Ops Engineers to deploy and monitor systems across environments

· Contribute to internal IP (e.g., RAG kits, prompt libraries, safety modules) and support demos

· Rotate into client delivery teams once frameworks and practices are learned

Qualifications

· 6–9 years of hands-on software engineering experience

· Experience with Python, LLM frameworks (LangChain, LlamaIndex, etc.), APIs, and containerized apps

· Understanding of GenAI patterns: RAG, agentic loops, embeddings, streaming, context injection

· Familiarity with observability (logging, prompt tracing, metrics), eval scaffolding, and CI/CD

· Bonus: UI integration (React, Next.js), insurance-specific workflow experience (claims, policy, underwriting)

Preferred Attributes

· Excited to work in agile, pod-based delivery teams

· Comfortable balancing experimentation with code quality

· Able to learn quickly, iterate fast, and collaborate across roles

· Ready to move between internal innovation and external delivery