AI Engineer

• Develop memory, context, state management, and retrieval layers.
  
• Build frameworks for prompts, tools, guardrails, retries, and workflow testing.
  
• Create agent evaluation and regression testing frameworks.
  
• Implement observability for traces, latency, errors, token usage, and quality.
  
• Build secure APIs using Python and FastAPI.
  
• Integrate agents with APIs, event streams, vector databases, and enterprise systems.
  
  
  

Requirements

• The ideal candidate should have 5+ years of experience in Python and backend development, with strong hands-on experience in FastAPI, REST APIs, and microservices.
  
• They should have at least 2+ years of experience building agentic or LLM applications using LangGraph, LangChain, or similar frameworks.
  
• Strong experience in memory and context engineering, agent evaluation, workflow testing, and AI observability is required.
  
• The candidate should also have experience working with MongoDB or other document databases, along with AWS or other cloud-native environments.
  
• Experience with Docker, Kubernetes, Kafka, AWS Bedrock, vector databases, MCP, knowledge graphs, and human-in-the-loop workflows will be preferred.
  
• Experience building AI applications in healthcare or another regulated domain.
  

Benefits

• Work on international projects: Be part of a global team working with clients from across the world.
  
• Regular team outings: Even with remote work, we believe in building strong team bonds through regular social and team-building events.
  
• Collaborative & growth-oriented: Learn from senior engineers, work in a collaborative environment, and grow professionally with opportunities for career development.
  
• Competitive Salary and Benefits