Senior AI Engineer

AI Agent Engineering

• Design and build AI agent pipelines, including multi-node LangGraph graphs.
• Implement intent routing, multi-turn conversational context, session state management, and tool integrations.
• Develop multi-step reasoning pipelines and graph-based agent workflows.

RAG & Knowledge Systems

• Build and maintain Retrieval-Augmented Generation (RAG) systems.
• Design vector search architectures, embedding pipelines, retrieval grounding, and chunking strategies.
• Implement hallucination mitigation techniques and retrieval evaluation frameworks.

LLM Integration & Optimization

• Integrate and optimize Large Language Models (LLMs) including OpenAI, Gemini, and Anthropic.
• Develop structured output workflows using JSON schemas.
• Create effective prompt engineering strategies, few-shot examples, and context window management solutions.
• Build provider-neutral client architectures to support multiple LLM vendors.

Full-Stack Development

• Design, develop, and deploy end-to-end product features.
• Build scalable FastAPI backends and React/Next.js frontends.
• Implement Server-Sent Events (SSE) streaming and REST API contracts.
• Deliver production-ready UI features independently without requiring dedicated frontend support.

Observability & Quality

• Own LLM observability including:
  • Token usage logging
  • Cost tracking
  • Fallback detection
  • Performance monitoring
  • Regression test suites
• Build evaluation pipelines and golden test suites to ensure AI quality and consistency.

Client & Product Collaboration

• Collaborate directly with clients and stakeholders to understand business requirements.
• Translate requirements into scalable, maintainable software solutions.
  • Keep technical documentation, specifications, and test coverage aligned with product changes.