Forward Deployed Engineer, Generative AI
| Full-time | Financial Services | New York, NY
About the role
Bounteous is seeking a Forward Deployed Engineer, Generative AI to support a
strategic engagement with the Fixed Income business (investment bank) in New
York.
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.
This role is not purely 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.
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.
What we are looking for
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.
Preferred qualifications
- 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
