Forward Deployed Engineer

Madison-Davis, LLC; New York (NY); On-site; USD 140,000 - 210,000; Full time

Job summary

Madison-Davis, LLC is expanding its AI Solutions function and hiring Forward Deployed Engineers to build AI-powered applications directly with investment and enterprise users in New York. This hands-on role blends Python development, AI, product thinking, and direct stakeholder interaction.

You will partner with portfolio managers, researchers, and business teams to translate problems into technical solutions, design production-grade AI applications, and own projects end-to-end from requirements

Qualifications

• 5+ years of professional software-engineering experience.
• Experience building software with business or non-engineering users.
• Ability to gather requirements and iterate based on user feedback.
• Experience with AWS services (S3, OpenSearch, DynamoDB).
• Kubernetes and modern CI/CD experience.
• Experience with unstructured or semi-structured data.
• Strong product instincts and prioritization of high-value features.
• Excellent communication and problem-solving skills.

Responsibilities

• Partner with investment professionals and users to identify AI opportunities.
• Translate business problems into technical requirements and products.
• Design and build production-grade AI applications and workflows.
• Create systems that analyze documents, filings, emails, and market data.
• Develop AI agents, prompts, reusable skills, and RAG workflows.
• Own projects from requirements through deployment and production adoption.
• Collaborate with AI platform teams to reuse patterns.
• Maintain engineering standards for testing, deployment, and production support.

Skills

Python development

Software engineering

Product thinking

Communication skills

Problem solving

Tools

AWS

Kubernetes

CI/CD

OpenSearch

DynamoDB

S3

Job description

A global investment organization is expanding its AI Solutions function and hiring Forward Deployed Engineers to build AI-powered applications directly with investment and enterprise users.

Rather than focusing exclusively on centralized AI infrastructure, this team embeds engineers directly with portfolio managers, researchers, technical teams, and corporate functions. Engineers identify high-value workflows, translate business problems into technical solutions, and take those solutions from initial concept through production use.

This is a hands-on software engineering role for someone who enjoys combining Python development, AI, product thinking, and direct stakeholder interaction.

Responsibilities

• Partner directly with investment professionals, researchers, and business users to identify high-value AI and workflow-automation opportunities.
• Translate ambiguous business problems into technical requirements and working products.
• Design and build production-grade AI applications and agentic workflows.
• Create systems that analyze documents, filings, emails, market information, reference data, and other real-world datasets.
• Develop AI agents, prompts, reusable skills, RAG workflows, and business-specific automations.
• Own projects from requirements and architecture through deployment, UAT, production adoption, and iteration.
• Partner with centralized AI platform teams and convert successful solutions into reusable patterns.
• Maintain strong engineering standards across testing, deployment, code quality, and production support.

Role Requirements

• 5+ years of professional software-engineering experience.
• Experience building software directly with business or non-engineering users.
• Ability to gather requirements and iterate based on real user feedback.
• AWS experience, including exposure to services such as S3, OpenSearch, or DynamoDB.
• Kubernetes and modern CI/CD experience.
• Experience working with unstructured or semi-structured data.
• Strong product instincts and ability to prioritize high-value features.
• Excellent communication and problem-solving skills.

Nice to Have

• Experience working directly with portfolio managers or investment-research teams.
• Discretionary macro, fixed-income, or fundamental-equity experience.
• Retrieval-Augmented Generation.
• MCP servers or agent orchestration.
• Claude Code or similar AI-assisted development tools.
• Product-management or roadmap-ownership experience.