À propos de ce poste Forward Deployed Engineer, Gen AI chez Bounteous
This is a highly embedded, client-facing engineering role. The FDE 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.
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.
What you will do
• Embed with banks Fixed Income teams in New York to understand business workflows, pain points, data availability, and AI opportunities.
• Partner with traders, sales, research, operations, risk, compliance, and technology stakeholders to translate business requirements into AI-enabled solutions.
• Design, prototype, and build generative AI applications using Python, OpenAI or Claude Agent SDK and other agentic frameworks (comparable LLM APIs), prompt engineering, MCP integrations, orchestration, retrieval-augmented generation, and agentic workflows.
• Develop AI solutions that support Fixed Income use cases such as knowledge retrieval, workflow automation, document analysis, trade support, client intelligence, operational exception handling, and management reporting.
• Build retrieval pipelines across structured and unstructured data, including research, policies, procedures, trade-related data, market commentary, client documents, and internal knowledge repositories.
• Apply prompt engineering techniques to improve model accuracy, consistency, explainability, and user trust.
• Design evaluation frameworks to test AI outputs for accuracy, completeness, hallucination risk, relevance, and compliance alignment.
• Work with technology and control teams to ensure solutions meet enterprise standards for security, data privacy, auditability, access control, and model governance.
• Communicate technical trade-offs clearly to both engineering teams and business stakeholders.
• Support user adoption by gathering feedback, refining workflows, and ensuring AI tools solve real business problems rather than becoming standalone experiments.
• Identify reusable patterns, accelerators, and components that can be scaled across other financial-services use cases.
Required qualifications
• 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.
Success in this role looks like:
• The Fixed Income business sees the FDE as a trusted technical partner who understands both the business context and the engineering requirements.
• AI use cases are prioritised based on measurable business value, feasibility, data readiness, and governance requirements.
• Prototypes move quickly but responsibly into controlled pilots and production pathways.
• AI outputs are tested, explainable, monitored, and aligned with enterprise risk and compliance expectations.
• Business users adopt the solutions because they improve real workflows reduce manual effort, and support better decision-making.
Why Bounteous
Bounteous is building practical, production-focused AI solutions for complex enterprise
environments. This role offers the opportunity to work at the intersection of generative
AI, capital markets, and business transformation, helping a leading financial institution
apply AI to high-value Fixed Income workflows in a responsible and scalable way