Senior Associate - Forward Deployed Engineer

New York LifeNew York, NY
$100,000 - $143,000Hybrid

About The Position

The Forward Deployed Engineer is an engineer embedded close to the business and outcome team, responsible for rapidly converting validated product intent, prototypes, and implementation specifications into working, production-ready technology. The role combines software engineering, systems thinking, AI-assisted development, integration, and direct collaboration with users and domain teams. Forward Deployed Engineers do not wait for traditional handoffs or fully decomposed tickets. They work from a prototype, PRD or implementation specification, enterprise architecture patterns, and direct feedback from the team to build, test, integrate, and refine solutions quickly. AI-assisted engineering is a core competency and is used throughout the software development lifecycle. The Forward Deployed Engineer turns product intent and implementation-grade specifications into working technology. The role is designed for a smaller, higher-leverage engineering model in which engineers use AI extensively, work directly with the business and analysts, and retain responsibility for system design, integration, quality, and production readiness.

Requirements

  • 5+ years of progressively responsible software engineering, application development, platform engineering, data engineering, or related technical experience.
  • Strong hands-on software engineering capability in one or more modern programming languages and frameworks.
  • Experience building and integrating production applications using APIs, cloud services, data platforms, and modern software architecture patterns.
  • Demonstrated ability to work from business intent and specifications rather than only from pre-defined technical tasks.
  • Experience with automated testing, CI/CD, observability, security, and production support practices.
  • Practical experience using AI-assisted software development tools and willingness to build with AI as a standard engineering practice.
  • Strong problem-solving, communication, and collaboration skills with the ability to work directly with business and technical stakeholders.

Nice To Haves

  • Experience building generative AI or agentic applications, including tool use, retrieval, orchestration, evaluation, or human-in-the-loop patterns.
  • Experience in financial services, insurance, finance, investments, or another regulated enterprise environment.
  • Experience in forward-deployed, consulting, startup, or product engineering environments requiring high autonomy and rapid iteration.
  • Experience with cloud-native architecture, APIs, data platforms, and enterprise integration.

Responsibilities

  • Build and iterate working software directly from validated prototypes, PRDs, specifications, and architecture patterns.
  • Use AI-assisted engineering tools extensively for code generation, refactoring, testing, documentation, debugging, and implementation planning while maintaining engineering accountability for the output.
  • Translate functional specifications into technical designs, components, APIs, integrations, data access patterns, and production-ready code.
  • Partner closely with Forward Deployed Analysts to resolve ambiguity and refine specifications as technical learning emerges.
  • Work directly with Product Owners, users, Domain SMEs, Data SMEs, architects, and strategic partner engineers in rapid feedback cycles.
  • Integrate applications and agents with enterprise APIs, data products, platforms, identity, security, and control capabilities.
  • Implement agentic and AI-enabled features using approved enterprise patterns, including tool integration, human checkpoints, observability, evaluation, and traceability.
  • Develop automated tests and participate in validation, deployment, production readiness, and post-release improvement.
  • Apply strong engineering judgment to distinguish prototype shortcuts from production requirements and close the gap deliberately.
  • Contribute reusable code, patterns, components, and engineering practices that can be adopted across outcome teams.

Benefits

  • leave programs
  • adoption assistance
  • student loan repayment programs
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