Forward Deployed Engineer/AI Python Engineer

Job DescriptionThis is a highly embedded, client-facing engineering role. The individual will play a role of Forward Deployed Engineer and will work directly with Fixed Income business users, technology teams, quants, operations, and control functions to identify high-value AI use cases, translate business workflows into technical designs, and build production-grade AI solutions. This role is not advisory. The successful candidate will be expected to sit close to the business, understand front-office and operational workflows, write code, test solutions, debug issues, and help move AI use cases from concept to controlled production adoption. The ideal candidate combines strong software engineering skills, practical generative AI experience, and a consultative approach to working with senior business stakeholders in a regulated financial-services environment.

• Bachelor’s degree in computer science, Engineering, Mathematics, Finance, or a related field, or equivalent practical experience.
• Strong hands-on experience with Python and modern software engineering practices.
• Practical experience building applications using Python, OpenAI or Claude Agent SDK and other agentic frameworks (comparable LLM APIs).
• Strong understanding of prompt engineering, including prompt design, prompt testing, grounding, context management, and output validation.
• Experience building AI or data-driven applications that use APIs, databases, cloud services, and enterprise data sources.
• Ability to work directly with business stakeholders, lead discovery discussions, clarify ambiguous requirements, and convert business problems into technical solutions.
• Strong communication skills and the ability to explain AI concepts, risks, and design choices in clear business language.
• Experience working in agile, fast-moving environments where prototypes must quickly evolve into production-ready solutions., * Financial-services experience, ideally within capital markets, Fixed Income, trading, sales, risk, operations, or banking technology.
• Familiarity with Fixed Income products such as rates, credit, securitised products, municipals, FX, or derivatives.
• Experience with retrieval-augmented generation, vector databases, embeddings, semantic search, and document intelligence.
• Experience designing AI evaluation frameworks, including test datasets, quality metrics, human review loops, and model performance monitoring.
• Familiarity with enterprise AI governance, model risk management, compliance review, data privacy, and regulatory expectations in financial services.
• Experience in a forward-deployed, consulting, client engineering, post-sales engineering, or technical delivery role.
• Exposure to cloud platforms, secure APIs, authentication/authorisation, and enterprise integration patterns.