Lead AI Engineer

Job title: Lead AI Engineer

We are seeking a Lead AI Engineer to serve as a core builder within the SMBS AI team, reporting to the Director, AI Solutions. The role involves owning AI agent solutions end-to-end—from design through production—ensuring production-grade quality and seamless integration into SimCorp’s AI ecosystem and governance frameworks.

What You'll Do

• Build AI agent solutions from technical design through production deployment, following the solution framework and standards defined by the Director, AI Solutions.
• Implement agent logic, prompt engineering, retrieval-augmented generation pipelines, and LLM API integrations.
• Develop and execute testing strategies for agent behavior, including edge-case handling, accuracy validation, and performance testing.
• Deliver production-ready agents within sprint timelines, managing technical complexity and communicating risks proactively.
• Own agents in production, including monitoring, incident response, and iterative improvement based on operator feedback and usage tracking.
• Resolve bugs and address agent behavior issues identified through operator feedback.
• Adapt agents when underlying data sources, operational processes, or platform infrastructure changes require updates.
• Participate in support rotations once multiple agents are live in production.
• Participate in code reviews, both giving and receiving, to maintain code quality.
• Support the Director, AI Solutions in evaluating new tools, frameworks, and approaches.
• Mentor AI Engineers on implementation practices, debugging approaches, and production readiness.
• Collaborate with Data Engineers to define data requirements and ensure agent data pipelines are reliable and performant.

What We're Looking For

• 5+ years of experience in software engineering with a focus on AI/ML, NLP, or data-intensive applications.
• Strong proficiency in Python and modern development tooling.
• Practical experience with LLM APIs, prompt engineering, RAG architectures, and vector databases.
• Experience deploying and maintaining AI/ML models or applications in production environments.
• Ability to work autonomously on complex implementations while aligning with broader solution standards.
• Strong ownership mindset: you are not done when the agent is deployed, but when it works reliably in production.
• Ability to communicate technical issues and agent behavior clearly to non-technical operators and stakeholders.
• Experience in financial services or operational environments is beneficial.

Nice to Have

• Experience in financial services or operational environments.

Compensation & Benefits

• Global hybrid work policy with 2 days in the office per week; remote work possible on other days.
• Growth and innovation: every 6th sprint reserved for planning and innovation.
• High degree of self-direction and autonomy.
• Inclusive and diverse company culture.
• Work-life balance and empowerment to shape processes.