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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Forward Deployed AI Full Stack Engineer - **Company:** Sapience AI Corporation - **Location:** Seattle, WA, United States - **Experience:** Expert - **Salary:** $156,000.0 - $168,000.0 - **Contract:** Permanent contract - **Skills:** JavaScript (Programming Language), Application Programming Interfaces (APIs), Artificial Intelligence, Amazon Web Services, Microsoft Azure, Cloud Computing, Information Engineering, Data Stores, Graph Database, Python (Programming Language), Node.Js, NoSQL, Search Technologies, Software Deployment, SQL Databases, TypeScript, Data Processing, ReactJS, Retrieval-Augmented Generation, Large Language Models, AI Coding Agents, Backend, Graphql, Machine Learning Operations, Front End Software Development, Data Pipelines - **Published:** October 28, 2026 - **Apply:** https://www.thejobnetwork.com/job/d89ec17b-2842-4a5e-9304-65760f4fe292/forward-deployed-ai-full-stack-engineer ## About the Role Who you areRequired qualifications * Five or more years building full stack applications in production. * Strong frontend skills with a modern framework, plus solid backend and data engineering. * Hands-on experience building with modern AI and ML systems, including LLMs and retrieval. * A track record of shipping complete, adopted products under real deadlines. * Comfort integrating third-party systems and APIs. * Care for security, permissions, and data protection across the stack. * Strong product instincts and attention to the member experience., * Experience deploying software at customer sites in a forward deployed model. * Familiarity with retrieval-augmented generation, vector search, and knowledge graphs. * Experience integrating CRM, AMS, or knowledge-platform systems. * Design sensibility and comfort collaborating closely with product design. * Exposure to agentic or neuro-symbolic AI systems. How you work * You lead with the member's real need and name the problem before the solution. * You move fast across the whole stack and keep quality where it counts. * You care about adoption, not just delivery. * You treat trust and data protection as design constraints. * You share reusable work so the whole team moves faster. Skills & Competencies * Full stack development across frontend, backend, and data. * Building member-facing AI experiences that people adopt. * Retrieval, embeddings, and grounding AI behavior in trusted data. * Integration across enterprise systems, identity, and permissions. * Adoption instrumentation and iterating on live experiences. * Secure-by-design engineering for sensitive community data. * Turning custom deployment work into reusable components. Services & Tools Experience * TypeScript and JavaScript with a modern frontend framework (React or similar). * Python or Node for backend services. * LLM orchestration and retrieval frameworks, plus vector and graph databases. * REST and GraphQL APIs and common integration patterns. * Cloud platforms (AWS, GCP, or Azure) and containers. * SQL and NoSQL data stores, plus analytics and instrumentation tooling. * CRM, AMS, and knowledge-base APIs, and Sapience AI's MINERVA and COGENT interfaces (trained on the job). Prior Experience & Background * Prior full stack engineering at a software or AI company, ideally including customer-facing delivery. * Experience owning products end to end, from data to interface. * A track record of shipping experiences that people actually adopt. * Experience mentoring or setting patterns for other engineers is a plus. ## Description A platform only creates value when people use it. For each community, that means an experience shaped around how they work, connected to their systems, and easy enough that expertise flows without friction. Building that experience end to end, fast, in a customer environment, takes an engineer who can move from data pipeline to interface without a handoff at every seam. The Forward Deployed AI Full Stack Engineer is that person. You deliver the whole solution, get it adopted, and carry what you learn back so the core platform serves the next community better. What you will own (Areas of Responsibility) You hold seven areas of responsibility inside the forward deployed team. Each one is yours to set direction on, build, and measure. 1. End-to-end solution delivery * Build complete solutions for customer deployments, from backend services to the member-facing interface. * Own the full path from problem to a running experience in the customer's environment. * Ship quickly under deployment timelines while keeping the result maintainable. 2. Member-facing experiences on MINERVA * Build the interfaces and workflows that let members search, act on, and share their community's expertise. * Design for adoption: fast time-to-value and low friction, so people actually use what you build. * Partner with product design to make the experience clear, trustworthy, and worth returning to. 3. Backend, data, and COGENT integration * Build the services, pipelines, and integrations that connect a deployment to the customer's systems and the KO graph. * Integrate deployment logic with the COGENT architecture's reasoning and retrieval. * Keep the data behind the experience current, accurate, and searchable. 4. Trust, security, and governance in the experience * Build access, permissions, and data handling so members only ever see what they should. * Make governance and provenance visible in the experience, so people trust what the platform tells them. * Meet the customer's security and privacy requirements across the whole stack. 5. Adoption instrumentation * Instrument the experience to show whether members are adopting it and reaching value. * Use those signals to improve the deployment after launch, not just before it. * Feed adoption learnings back to product and the field. 6. Reusable components and field leverage * Turn repeated deployment work into reusable components, templates, and patterns. * Contribute improvements back into the core platform so the next deployment starts further ahead. * Keep the field team's shared toolkit current as the platform moves through each GR/GA milestone. 7. Collaboration and handoff * Work alongside forward deployed sales and backend engineers to deliver complete solutions. * Leave the customer's team able to run and extend the experience. * Hand off cleanly to customer success with the documentation they need. AI-augmented ways of working You build with AI across the stack. You use AI coding assistants and Sapience AI's own systems to accelerate delivery, prototype interfaces, and reason through unfamiliar code, while you own the architecture, the experience, and the quality of what ships. The standard is human in partnership: AI accelerates the work, you own the judgment, the interpretation, and the call. The people who create the most value here are not the ones producing the most output. They are the ones turning evidence into clear, durable decisions. What this role is not To keep the boundary clear: * This is not a core platform-only role. You build in customer environments and feed patterns back, rather than working solely on the central codebase. * This is not a design-only or backend-only role. You own the whole stack, from data to interface. * This is not a research role. You apply and deploy AI in production rather than developing new model architectures. * This is not a throwaway-prototype role. You ship experiences members adopt and others can maintain., You work most closely with the forward deployed sales and backend engineers, Applied AI, Product Design, and the customer's own teams. You partner with core platform teams to feed reusable patterns back into MINERVA and COGENT.