Forward Deployed AI Engineer
Contract Independent
Contract W2
Contract Corp To Corp
12 Months
No Travel Required
On-site
Depends on Experience
Zealogics
Fitment
Dice Job Match Score™
👾 Reticulating splines...
Job Details
Skills
- Roles and Responsibilities 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 Bachelors 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
- 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
- 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.
- Cloud Computing
- Customer Engineering
- Customer Intelligence
- Agile
- Artificial Intelligence
- Authentication
- Banking
- Evaluation
- Microsoft Certified Professional
- Risk Management
- Sales Engineering
- Software Design
- Performance Monitoring
- Privacy
- Prototyping
- Python
- Regulatory Compliance
- Financial Services
- Generative Artificial Intelligence (AI)
- Management
- Management Reporting
- Capital Market
- Communication
- Database
- Unstructured Data
- Workflow
- Derivatives
- Enterprise Integration
- SDK
- Software Engineering
- Testing
- Use Cases
- Forward Deployed AI Engineer
- Forward Deployed Engineer
- Deployed AI Engineer
Summary
Roles and Responsibilities
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.
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.
Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.
- Dice Id: 90824428
- Position Id: 9058390
- Posted 3 hours ago
Company Info
About Zealogics
Welcome to Zealogics
Zealogics LLC provides a broad range of IT consulting, systems implementation and application outsourcing services through an optimized global delivery model. Zealogics also built deep knowledge of traditional product engineering across mechanical, electronics and software platforms, to enable clients to navigate their digital transformation.
Zealogics value engineering techniques, automation frameworks, and reference models are refined through engagements with Fortune 500 enterprises and OEMs. We combine customer-centric product strategies with a collaborative approach to execution. It helps harmonize processes, identify bottlenecks, and eliminate non-value adding tasks to deliver world-class products.
We also focus on connecting the right people with the right positions whether for a full-time career opportunity or a temporary assignment. Our long-term relationships with employees and clients have been built in an environment of integrity and commitment, with a shared goal of mutual success. We hire talented people to solve a wide array of IT and Engineering challenges that our clients face day to day. Here at Zealogics we provide the best services for the best price in town. That s our guarantee.
Careers
Website
Zealogics LLC provides a broad range of IT consulting, systems implementation and application outsourcing services through an optimized global delivery model. Zealogics also built deep knowledge of traditional product engineering across mechanical, electronics and software platforms, to enable clients to navigate their digital transformation.
Zealogics value engineering techniques, automation frameworks, and reference models are refined through engagements with Fortune 500 enterprises and OEMs. We combine customer-centric product strategies with a collaborative approach to execution. It helps harmonize processes, identify bottlenecks, and eliminate non-value adding tasks to deliver world-class products.
We also focus on connecting the right people with the right positions whether for a full-time career opportunity or a temporary assignment. Our long-term relationships with employees and clients have been built in an environment of integrity and commitment, with a shared goal of mutual success. We hire talented people to solve a wide array of IT and Engineering challenges that our clients face day to day. Here at Zealogics we provide the best services for the best price in town. That s our guarantee.
Careers
Website
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