We’re looking for an AI Engineer who thrives at the intersection of applied machine learning and production software engineering. You will design, build, and operate intelligent systems powered by large language models from agentic workflows and RAG pipelines to multi-step LangGraph agents deployed reliably on AWS.

This is a hands-on engineering role. You will own features end-to-end: collaborating with product and data teams to define requirements, implementing solutions with clean Python, and shipping them to production. You care about observability, cost efficiency, and measurable agent quality not just getting demos to work.

What You’ll Do

• Design and build production LLM-powered features, including multi-step agentic workflows, RAG pipelines, and tool-augmented assistants.
• Develop and maintain LangGraph agents with well-defined state management, checkpointing, and human-in-the-loop patterns.
• Integrate AWS Bedrock to invoke foundation models  , configure Guardrails, and leverage Knowledge Bases and Agents.
• Architect and operate AI workloads on AWS across Lambda, ECS/Fargate, S3, DynamoDB/RDS, and CloudWatch.
• Set up and manage MCP (Model Context Protocol) servers and clients to extend agent capabilities with external tools and data sources.
• Own prompt engineering and evaluation: define metrics, run experiments in Braintrust, LangSmith, or Promptfoo, and iterate systematically.
• Build and maintain RAG architectures: manage embeddings, vector databases (OpenSearch, pgvector, Pinecone), and chunking strategies.
• Maintain high engineering standards: write typed, tested Python; enforce CI/CD pipelines; manage infrastructure with CDK, Terraform, or CloudFormation.
• Work with  Code and comparable agentic coding tools to accelerate development — authoring CLAUDE.md files, custom slash commands, and team workflow integrations.
• Monitor cost, latency, and reliability of LLM workloads; propose and implement optimizations.

Minimum Requirements

• 3+ years of professional software engineering experience, with at least 1 year focused on building and operating production AI/LLM applications.
• Hands-on experience with  Code or comparable agentic coding tools: writing CLAUDE.md files, building custom slash commands, configuring MCP servers, and integrating them into team workflows.
• Practical experience invoking foundation models via the Bedrock Runtime API, working with models on Bedrock, and understanding Bedrock Guardrails, Knowledge Bases, or Agents.
• Solid working knowledge of IAM, Lambda, ECS/Fargate, S3, DynamoDB or RDS, CloudWatch, and VPC networking. Comfortable deploying and operating services in production.
• Production experience designing stateful multi-step agents: building graph workflows with nodes and edges, managing state and checkpointing, and handling tool calls and human-in-the-loop patterns.

• Are you interested in this position?

   

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