Full-Stack Developer (AI-Augmented Engineering)

Who is Forcepoint

Forcepoint simplifies security for global businesses and governments. Forcepoint's all-in-one, truly cloud-native platform makes it easy to adopt Zero Trust and prevent the theft or loss of sensitive data and intellectual property no matter where people are working. 20+ years in business. 2.7k employees. 150 countries. 11k+ customers. 300+ patents. If our mission excites you, you're in the right place we want you to bring your own energy to help us create a safer world. All we're missing is you!

About the Role

We're looking for a full-stack developer to join our growing engineering team. This is primarily a product engineering role - you'll design, build, and maintain web applications end to end - but you'll do it in an AI-native way, relying on agent frameworks and AI coding assistants throughout the development lifecycle - not as a bonus skill, but as a core requirement. You're expected to understand how the underlying models work well enough to use them effectively and evaluate their output critically.

Key Responsibilities

• Design, build, and maintain production web applications across the full stack (frontend, backend, and data layer).
• Use AI coding assistants (Claude Code, Cursor, GitHub Copilot, or similar) throughout the SDLC - from spec and scaffolding through implementation, testing, and review - rather than only for isolated snippets.
• Integrate LLM-powered features and lightweight agentic workflows into product surfaces where they add real user or operational value.
• Work with agent frameworks (LangChain, CrewAI, AutoGen, or similar) to build or extend automation that connects LLMs to APIs, data sources, and internal tools.
• Critically review, debug, and refactor AI-generated code - your own and teammates - with full ownership and understanding of what ships.
• Write clean, maintainable, well-tested code with unit and integration tests, including for AI-generated contributions.
• Collaborate with product and engineering peers to scope features, define API contracts, and ship reliably under deadlines.
• Document designs, decisions, and AI-assisted workflows clearly for the team.

Required Qualifications

• 4+ years of professional full-stack development experience (e.g., React on the frontend Python/Go/Rust on the backend).
• Working understanding of how LLMs function at a practical level - tokens, context windows, embeddings, prompting, and the general shape of what models can and can't reliably do.
• Hands-on experience with at least one agent framework (LangChain, CrewAI, AutoGen, or similar) - production use preferred, personal/academic projects acceptable.
• Fluent with AI coding assistants (Claude Code, Cursor, GitHub Copilot, or similar) as a daily part of your workflow - skilled at providing clear context to get production-quality output.
• Strong code ownership - able to explain and defend every line you submit regardless of how it was generated, and to catch subtly incorrect AI output.
• Familiarity with AI-native SDLC practices - using AI assistance across planning, coding, testing, and review, not just code completion.
• Basic prompt engineering and tool/function-calling fundamentals for working with LLM APIs (OpenAI, Anthropic, Gemini, or open-source equivalents).
• Comfort with REST APIs, JSON, relational databases, and version control (Git).

Nice to Have

• Experience shipping an LLM-powered feature (chat, RAG, summarization, or similar) inside a production web app.
• Exposure to vector databases or semantic search.
• Familiarity with workflow automation tools (n8n, Zapier, Airflow).
• Comfort with both a compiled backend language (Go/Rust) and Python.
• Any personal AI projects, bots, or automation tools you've shipped.