Senior AI Engineer

At Mitratech, we are a team of innovators focused on building world-class products that simplify operations in the Legal, Risk, Compliance, and HR functions. We are a close-knit, globally dispersed team that thrives in an ecosystem that supports individual excellence and takes pride in its diverse and inclusive work culture centered around great people practices, learning opportunities, and having fun! Our culture is the ideal blend of entrepreneurial spirit and enterprise investment, enabling the chance to move at a rapid pace with some of the most complex, leading-edge technologies available. For over 35 years, the experts at Mitratech have been focused on solving the complex needs. Today, we serve 20,000 client companies of all sizes globally, representing 30% of the Fortune 500 and over 500,000 users in over 160 countries. As we continue to grow, we’re always looking for resourceful, enthusiastic, and fresh perspectives. Join our global team and see what makes Mitratech a truly exceptional place to work! Job Overview We're hiring a Senior AI Engineer to design, build, and operate intelligent agent systems end-to-end on our AWS-native GenAI platform. You'll own major agent services from design through stable operations, design agent workflows and RAG architectures for team-level use, define the testing and reliability practices for your areas, and mentor across the team. Agents are the headline, but this is a full-stack platform role: you ship the FastAPI service, the Terraform, the MCP server, and the eval harness behind the agent — and you set the bar for how they're built. Essential Duties & Responsibilities : - Design and own LLM-powered agents end-to-end for internal tooling, customer-facing features, and workflow automation — built on Bedrock with LangChain/LangGraph and the langchain-aws/-anthropic/-core stack - Design agent workflows and RAG architectures for team-level use; influence team design beyond your own services - Build and operate MCP servers that expose company data and services as structured tools for AI models - Define the testing, reliability, and operational practices for your areas; own delivery and on-call quality for major services - Stand up evaluation pipelines (Langfuse + eval harnesses) and prompt-versioning practices, and use them to drive reliability and cost/quality improvements - Lead design reviews, mentor across the team, and drive improvements in engineering practice - Collaborate with product, data, and platform teams to scope and deliver agent-based solutions, applying platform patterns and governance hooks correctly Requirements & Skills: - 5+ years of software engineering experience, with multiple years building and operating LLM or AI agent systems in production - Expert-level Python and service development (async, FastAPI, Pydantic v2), with a track record of owning services end-to-end - Deep GenAI/LLM application experience — designing RAG architectures and agent workflows, ideally with Claude via Amazon Bedrock or the Anthropic API - Strong AWS engineering (Bedrock, Lambda, ECS, API Gateway, and the surrounding services) - Hands-on agent tooling: LangChain/LangGraph and MCP (building and operating tool/resource servers) - Terraform / IaC and containerized delivery through CI/CD - Strong data-layer experience (Redis, Snowflake, DynamoDB, Postgres/Aurora) via async SQLAlchemy - Identity and app-security fundamentals (JWT/OAuth, secrets management) - Production observability and LLM evaluation experience (tracing, evals, latency/cost/quality metrics) - Demonstrated ability to mentor engineers, lead design reviews, and set engineering practices Nice to have: - Data warehouse engineering (Snowflake) - NoSQL / document databases (MongoDB) - Frontend / web UI development (React 19, TypeScript) — used in the platform but not expected for this role - Responsible AI / governance experience We will disclose intended pay ranges in our job ads for US-based opportunities – This role can be pe…