AI Machine Learning Engineer

Overview

We are seeking a Senior AI / Machine Learning Engineer to join the team. This position emphasizes backend engineering, cloud infrastructure, and AI/LLM integration
, with less focus on model training and more on designing, building, and scaling applications around AI capabilities.

• Design and build AI-driven backend services and applications using Python
• Develop and deploy LLM-powered agents to support retirement services use cases
• Build stateful AI agents
  , including custom tools and workflows using MCP (Model Context Protocol)
• Design and implement RESTful APIs using FastAPI, including async patterns
• Build scalable, containerized services optimized for serverless environments
• Implement RAG architectures using vector databases such as Pinecone or Qdrant
• Collaborate closely with data engineering, platform, and security teams
• Ensure production-ready solutions with proper authentication, retries, and fault tolerance
• Use Infrastructure as Code to provision and manage cloud resources

• 6+ years of Python backend engineering experience
• Strong experience with Async
  
  IO (async/await),
  Pydantic
  , and FastAPI
• 4+ years of Docker containerization, including multi-stage builds and optimization
• 5+ years designing API client architectures
  , including robust adapters for internal/corporate gateways
• 4+ years working with AWS compute and networking services (ECS Fargate, ECR, API Gateway, Route 53)
• 4+ years with AWS security services (IAM, Secrets Manager, VPC configuration)
• 3+ years using Infrastructure as Code (Terraform or AWS CDK)

• 2+ years integrating LLMs (Azure OpenAI / Azure AI Gateway preferred; 1 year acceptable for urgent needs)
• 2+ years working with agent frameworks such as Lang Chain, Llama Index, or Strands SDK
• Hands-on experience building stateful agents
  , custom tools, and workflows
• Experience with Model Context Protocol (MCP)
• 1+ year experience with vector databases and Retrieval Augmented Generation (RAG)

• Experience building AI applications in regulated or enterprise environments
• Familiarity with retirement services or financial services domains
• Strong understanding of production-grade AI system design