Senior AI Engineer

About You 

Are you looking for an opportunity to work on meaningful, cutting-edge projects at the intersection of agentic AI and responsible business conduct? Did you wonder what it would be like to work at a company where your contribution has a real, measurable impact - and you are rewarded for it?

If you have a passion for building production-grade AI agents, MCP-based tool ecosystems, and data-rich AI workflows, then this is the perfect role for you! We value autonomy, allowing you to bring your innovative ideas to fruition in an inclusive, feedback-oriented environment. Your work on agentic systems will directly contribute to advancing gloabl corporate responsibility through technology.

Your Responsibilities 

As our new Senior AI Engineer, you will play a crucial role in developing state-of-the-art agentic systems and AI integrations within RepRisk’s Agentic delivery team. You will contribute to the design, implementation and operation of agentic and AI products within the company. Moreover, you will be: 

• Designing and building single- and multi-agent production systems with planning, memory, and tool-use capabilities that meet regulated-industry compliance and auditability standards.
• Building and operating MCP (Model Context Protocol) servers using FastMCP and platform providers such as Databricks or Snowflake, with secure schemas and role-based permissions.
• Developing agentic workflows using LangChain and LangGraph, with robust prompt engineering, tool-use, and multi-agent coordination patterns.
• Implementing testing, evaluation, monitoring, and observability best practices for production agent systems (LangSmith / LangFuse, structured tracing, offline and online evaluation).
• Developing, integrating, and maintaining LLM-powered microservices and APIs (Python, FastAPI, gRPC, Postgres) as part of broader production applications deployed on AWS.
• Identifying, testing, and adopting state-of-the-art advancements in LLMs and autonomous agent architectures (e.g. reflection, planning, multi-agent coordination, AWS Bedrock and Bedrock AgentCore).
• Collaborating closely with the Product Manager, Tech Lead, and domain experts to align technical solutions with user needs and business goals; supporting discovery, proposing improvements, and showing initiative beyond the assigned scope.