About the Role :

We are looking for a Senior AI Engineer to design and build production-grade LLM and agentic AI systems. The role will focus on AI orchestration, evaluation, reliable structured outputs, production deployment, retrieval systems, and observability of AI/agent behavior.

Key Responsibilities :

- Design, develop, and deploy production-grade LLM and agentic AI applications.

- Build and maintain agent orchestration workflows using frameworks such as LangGraph.

- Develop reliable AI workflows with structured outputs and schema validation.

- Design and implement evaluation (Evals) frameworks to assess model and agent performance.

- Work on improving reliable and predictable model behavior in production environments.

- Develop AI services using Python, with exposure to Golang and TypeScript.

- Work with self-hosted inference technologies and optimize model serving.

- Build and integrate retrieval systems for AI applications.

- Implement observability and monitoring for LLM and agent behavior.

- Contribute to scalable AI architecture and production deployment practices.

Mandatory Skills :

- Strong experience building LLM systems

- Production deployment of AI/ML applications

- Agent orchestration

- LangGraph

- Python

- Golang

- TypeScript

- Evals / AI evaluation

- Structured output

- Schema validation

- Understanding of reliable model behavior

Good-to-Have Skills :

- Temporal, Cadence, AWS Step Functions, vLLM, TGI, Model quantization, GPU scheduling, Retrieval systems, OCR, Layout parsing, PDF extraction, Audit trails, Compliance reporting

Candidate Profile :

- 3 - 9 years of relevant professional experience.

- Strong hands-on experience developing and deploying LLM/Generative AI applications.

- Experience taking AI/agentic systems from development into production environments.

- Strong programming skills in Python; experience with Golang and TypeScript is required.

- Practical experience with agent frameworks/orchestration, particularly LangGraph.

- Understanding of evaluation, structured outputs, validation, and reliability in AI systems.

- Ability to work on complex AI engineering problems involving inference, retrieval, and observability.