AI Engineer - Consulting Tools

Responsibilities

• Consulting Tool Development
• Design and build AI-powered tools supporting consulting delivery - including data mapping, validation, documentation generation, and workflow automation.
• Progress towards building complete, deployable tools - web apps, APIs, and agent integrations - as your skills develop.
• Translate consultant problems into working solutions, developing your ability to scope and frame engineering challenges independently over time.
• Support the progression of solutions from MVP to stable, reusable tools.
• Learn to write robust, understandable, and maintainable code.
• Apply reuse principles - solutions must work across clients, not single engagements.
• Engineering & Integration
• Integrate AI capabilities with SimCorp tools, workflows, APIs, enterprise systems, and data pipelines.
• Build an understanding of real client environments and delivery constraints.
• Participate in code reviews as both reviewer and reviewee.
• Work within defined delivery governance and contribute to standardization.
• AI Engineering
• Apply prompting strategies, retrieval-augmented generation (RAG), and evaluation approaches.
• Learn to design AI behavior that is predictable, testable, and safe.
• Contribute to evaluation frameworks that validate output quality.
• Develop awareness of LLM limitations (hallucination, sensitivity, consistency).
• Research & Continuous Learning
• Stay current with the rapidly evolving AI landscape - new models, tools, techniques, and frameworks.
• Read and digest research papers, technical blogs, and vendor releases, and share relevant findings with the team.
• Evaluate emerging tools and approaches for their practical fit with consulting delivery.
• Run small experiments and proofs-of-concept to test new capabilities before adopting them.
• Attend conferences, webinars, and industry events, and feed learnings back into the team's practices.
• Collaboration & Community
• Build relationships and collaborate with AI engineers and technical teams across SimCorp.
• Share approaches, reusable components, and lessons learned with the wider internal AI community.
• Contribute to and draw on cross-team practices, standards, and tooling.
• Participate in internal AI forums, guilds, and communities of practice.
• Delivery Support & Adoption
• Support teams during active tool usage and identify issues.
• Participate in feedback loops with consultants.
• Contribute to iterative refinement based on real-world use.
• Knowledge & Reuse
• Contribute to internal toolsets and the accelerator library.
• Document solutions, patterns, and lessons learned.
• Participate in internal training and capability development.
• Required Qualifications
• What a strong candidate genuinely brings on day one.
• We don't expect any candidate to meet every point below. If you have a strong core and are excited to grow into the rest, we encourage you to apply.
• Core Engineering
• A recent (or final-year) BSc or MSc in Computer Science, Software Engineering, or a related field.
• A solid foundation in Python.
• Some experience building and consuming REST APIs.
• Exposure to web development - frontend and/or backend (e.g. React/TypeScript, or Python/Node back ends).
• Familiarity with Git and collaborative workflows (branches, pull requests, code review).
• Exposure to a cloud platform (Azure or AWS).
• AI & LLM Exposure
• Hands-on exposure to developing AI solutions through coursework, projects, or internships.
• Awareness of prompt engineering and RAG approaches.
• An understanding of LLM behaviour and associated risks.
• Mindset & Problem Solving
• Genuine curiosity about AI and a habit of self-directed learning - the field moves fast, and staying current is part of the job.
• Ability to break down ambiguous problems.
• Comfortable asking for help and incorporating feedback.
• A focus on buil

Additional Information

Why This Role Matters SimCorp's consulting delivery involves solving complex, recurring problems across dozens of clients. The purpose of this team is to turn those recurring challenges into scalable, AI-enabled capabilities - reducing manual effort, increasing consistency, and raising quality across engagements. As an AI Engineer, you will contribute to that mission from the start - building real AI tools used in live projects, with the support and structure to develop into a confident, independent engineer over time. As the team grows, you will have the opportunity to influence how these tools are designed, built, and used across consulting delivery - not just contribute to them. Your Growth Path This is a development role. You will start by contributing to existing tools and learning the stack, the team, and real consulting delivery, and grow towards designing and shipping complete tools - web apps, APIs, and agent integrations - independently. We expect you to grow into the full breadth of the work over time, with mentorship throughout; we are not expecting you to arrive with all of it. How quickly you progress will depend on you, and we will support that growth rather than hold it to a fixed timetable.

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