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 RepRisks 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.

Qualifications :

You Offer

• Experience: 5 years of hands-on software engineering experience with 2-3 years building AI agents in production environments ideally for high-stakes or regulated industries (finance legal healthcare etc.).
• Education: A Masters degree or higher in Computer Science Engineering Statistics or a related STEM field (or equivalent practical experience).
• Agentic frameworks: Strong hands-on experience building agents with LangChain and LangGraph (or equivalent orchestration frameworks) including planning memory tool-use and multi-agent patterns.
• MCP expertise: Proven experience building and operating MCP (Model Context Protocol) servers using FastMCP or on platform providers such as Databricks or Snowflake with secure schemas authentication and role-based permissions.
• Python & backend: Expert-level Python skills and strong engineering fundamentals across backend systems APIs and data pipelines (FastAPI Postgres / SQLAlchemy gRPC async IO Databricks testing).
• Observability & evaluation: Proficiency with observability platforms and evaluation frameworks for LLM applications (e.g. LangSmith LangFuse) performance profiling and optimization techniques for AI systems.
• Engineering fundamentals: Solid understanding of software design principles (SOLID DRY KISS) Clean Code and common architecture patterns; ability to translate them into maintainable production code.
• Ownership & drive: High sense of product ownership taking full responsibility for assigned work end-to-end supporting the Tech Lead and PM in discoveries proposing improvements to existing services and showing initiative. Strong responsiveness and reliability.
• Continuous learner: Stays on top of the latest best practices in AI engineering and shares knowledge across the team.

Additionally the following are a plus:

• AWS Bedrock & AgentCore: hands-on experience with AWS Bedrock and Bedrock AgentCore for managed agent deployments and tool orchestration.
• Kubernetes: experience running containerized workloads on Kubernetes in production.
• ML engineering: experience with classical ML / LLM engineering on large datasets fine-tuning retrieval and summarization pipelines over ESG-scale corpora.
• Coding agents: experience building software solutions with the support of coding agents (Claude Code Cursor etc.) and leveraging them to accelerate delivery.
• Mentorship: experience mentoring engineers and providing thoughtful constructive feedback.

Additional Information :

Please note that we will only consider candidates with a valid work permit.

Remote Work :

No

Employment Type :

Full-time

Experience: years
Vacancy: 1