Full Stack / Forward Deployed AI Product Engineer (.NET & React, Agentic AI-Enabled SDLC) – Onsite (NJ, NYC), USA
Position Overview
We are seeking a highly capable Full Stack Software Developer with strong expertise in .NET (backend) and React (frontend), combined with hands-on experience in AI-assisted software development and agentic automation. This role operates as a forward deployed product engineer — sitting close to the business, translating real problems into working software, and playing a critical part in advancing our AI-driven SDLC by working closely with our internal AI team to refine frameworks, accelerate delivery, and improve software quality.
The ideal candidate brings practical experience with AI-native tools such as Claude Code, Cursor, Azure AI Foundry, Cowork, and agentic AI services, and a strong understanding of how AI agents can be embedded across the software development lifecycle to drive efficiency and innovation. Equally important is product sense — the judgment to decide what is worth building, not just how to build it. We are looking for a professional who has already deployed AI automations in production, is motivated to deepen hands-on AI skills, stays ahead of the rapidly evolving AI landscape, and treats AI-driven development as a career accelerator.
This is a Product + Engineering hybrid role. You will be embedded directly with stakeholders, own outcomes end to end, and be measured on the automations and products you ship.
Work Environment
- Location: Onsite, United States - 3 days per week in-office across NJ (Summit) and NYC (Midtown) Offices.
- Engagement Model: High-touch collaboration with AI, Product, and Engineering teams
- Focus: Driving enterprise adoption of AI-enabled software development practices
- Role Type: Product + Engineering hybrid — Forward Deployed AI Product Engineer.
KEY RESPONSIBILITIES:
Full Stack Development;
- Design, develop, and maintain scalable applications using .NET (C#, APIs, backend services) and React (modern frontend frameworks).
- Build responsive, high-performance user interfaces and robust backend services.
- Ensure code quality, performance optimization, and adherence to enterprise architecture standards.
AI-Driven SDLC Enablement;
- Apply AI tools (e.g., Cursor, Claude Code) to accelerate development, including code generation, debugging, and documentation.
- Integrate AI across SDLC phases—requirements, design, coding, testing, and deployment.
- Leverage structured AI SDLC frameworks (e.g., BMAD or similar) to optimize development workflows.
- Contribute to evolving best practices for AI-assisted engineering.
Agentic Automation & AI Engineering;
- Design, build, and deploy AI agents that automate real engineering and business workflows end to end — not just assist with them.
- Automate coding agents: orchestrate Claude Code and similar agentic tools into repeatable, reviewable pipelines — scaffolding, refactors, test generation, migrations, and documentation.
- Build multi-step agent workflows with tool use, context management, evaluation, and guardrails.
- Own the full automation lifecycle: identify the manual process, automate it by building AI agents, measure the time and cost saved, and harden it for production.
- Drive AI innovation — prototype rapidly with emerging AI-native tools and bring the ones that work into the organization’s standard practice.
Forward Deployed Product Engineering;
- Embed directly with business, product, and end-user stakeholders to understand the problem before writing code.
- Apply product sense to scope, sequence, and prioritize work — ship the smallest thing that solves the real problem.
- Move quickly between discovery, prototype, and production; demo working software rather than writing specs about it.
- Own outcomes end to end: requirements, build, deployment, adoption, and measurable business impact.
Framework Collaboration & Innovation;
- Work alongside the internal AI team to refine, validate, and pressure-test existing AI development frameworks.
- Help define and shape the organization’s AI-driven development approach in real time.
- Participate in pilot programs, experimentation, and continuous improvement initiatives.
Solution Design & Business Alignment;
- Translate business requirements into scalable, secure, and maintainable technical solutions.
- Collaborate with product owners, architects, and business stakeholders to ensure alignment and clarity.
- Provide input on system design, architecture, and technical trade-offs.
Onsite Execution & Agile Delivery;
- Operate onsite in the USA to enable rapid feedback loops and faster decision-making.
- Support iterative delivery, quick prototyping, and continuous alignment with stakeholders.
- Participate in Agile ceremonies and cross-functional collaboration.
Required Qualifications;
- Bachelor’s degree in Computer Science, Engineering, or equivalent experience.
- 5+ years of experience as a Full Stack Developer.
- Strong proficiency in:
- .NET / C# / ASP.NET Core
- React / JavaScript / TypeScript
- Experience building and consuming RESTful APIs and microservices architectures.
- Hands-on experience with AI-assisted development tools such as Claude Code or Cursor — used beyond autocomplete, as agents that execute multi-step work.
- Demonstrated drive to continuously build AI skills and apply them in day-to-day engineering work.
- Strong understanding of modern SDLC practices (Agile, DevOps, CI/CD).
- Hands-on experience with AI-native tools and platforms such as Claude Code, Azure AI Foundry, Cowork, and agentic AI services.
- Demonstrated experience deploying AI automations into production — with specific examples of what was automated and the impact delivered.
- Proven ability to automate AI functions and coding agents: prompt and context engineering, agent orchestration, tool/MCP integration, and evaluation.
- Strong product sense — able to question requirements, prioritize ruthlessly, and make judgment calls on what to build.
- Comfort operating as a forward deployed engineer: stakeholder-facing, ambiguous problems, high autonomy, fast feedback loops.
Preferred Qualifications;
- Experience with AI SDLC frameworks (e.g., BMAD or equivalent).
- Exposure to prompt-driven development and automated code generation workflows.
- Experience contributing to enterprise-scale framework or platform development.
- Familiarity with cloud platforms (Azure, AWS) and modern DevOps pipelines.
- Experience at leading technology or Fortune-scale companies such as Microsoft, Google, Capital One, ServiceNow, or Walmart — or a track record of operating at that level.
- Master’s degree in a technical field from a US university, or an MBA on top of a technical foundation.
- 3–5 years of experience in a solution architect capacity, or a technically strong product/program/project management background moving deeper into AI-enabled engineering.
- Experience building agent frameworks, MCP servers/tools, or internal AI platforms used by other engineers.
- Track record of AI innovation — internal tooling, hackathon wins, open source contributions, or published work on agentic systems.
- Experience in a forward deployed engineer, solutions engineer, or founding engineer capacity at an AI or high-growth product company.
- Experience shipping products where you also owned the product decision, not only the implementation.
Key Competencies;
- Strong problem-solving and analytical skills
- Ability to work in fast-paced, evolving AI-driven environments
- Excellent communication and cross-functional collaboration skills
- Adaptability and eagerness to learn emerging AI technologies
- Ownership mindset with focus on outcomes and delivery
- Product sense — strong instincts for user needs, prioritization, and what “done” should actually mean.
- Agentic thinking — defaults to “can an agent do this repeatedly?” instead of doing it manually.
- Comfort with ambiguity and direct stakeholder exposure as a forward deployed engineer.