Forward Deployed Engineer
Location: San Francisco · Category: Engineering & Development · Seniority: Mid-Level · Posted: September 10, 2026 · Verified: Oct 6, 2026
Role Overview & Description
Track team expansion and market signals for Cargo
Polaris7 monitors open roles, strategic market movements, and M&A developments in real time. Get automated intelligence briefings on Cargo and benchmark against direct competitors.
Cargo
getcargo.aiProgrammable GTM infrastructure for revenue operations teams.
Unlock full company profile, competitors & live market signals for Cargo
Similar Positions in DACH
Related roles across advertising, media, and data
This forward deployed engineer role partners with Strategic Project Leads to scope and build custom technical solutions for AI labs and product teams, turning fuzzy customer briefs into technical plans. The engineer will build capture flows, data pipelines, and delivery systems across web, mobile, and backend, while owning technical decisions and moving repeat builds into the core platform. Requires 7+ years of full-stack production experience, direct customer-facing work, and hands-on experience with AI coding agents and LLMs.
This role leads complex end-to-end deployments of frontier models in production for strategic customers. The engineer owns discovery, technical scoping, system design, build, and production rollout, working closely with customer engineering teams. Requires 5+ years of engineering experience, production-grade coding skills in Python or JavaScript, and experience with LLM-powered systems.
This Forward Deployed Engineer role focuses on building and deploying AI systems for legal work, embedding with law firms and legal teams to identify high-value use cases and rapidly prototype solutions. The engineer will own technical work from discovery through production adoption, building full-stack systems and translating customer workflows into product feedback. Requires 5+ years of software engineering experience with customer-facing ownership in regulated industries, and experience deploying LLM-powered systems.
Designs, builds, and deploys agentic workflows powered by Large Language Models for enterprise customers, integrating LLMs with tools, APIs, and sensitive data sources. Owns the full product lifecycle from prototyping to production-grade AI agents, ensuring reliability, observability, and safety. Requires Applied AI experience and close collaboration with clients in sectors like finance, healthcare, and telecommunications.
More Positions at Cargo
3 more open roles
This role owns adoption, value realization, relationship health, renewal readiness, and expansion after go-live for enterprise AI customers. Responsibilities include building success plans around measurable operational outcomes, driving adoption, leading evidence-based business reviews, and identifying renewal risks early. Requires enterprise customer success or technical account management experience, technical fluency with APIs and integrations, and clear executive communication.
This role owns the go-to-market narrative and positioning for Sainapse, an AI product, including building buyer personas, core messaging, and sales enablement assets like case studies and battlecards. Requires strong B2B product marketing experience for technical enterprise products, excellent writing skills, and the ability to understand APIs, workflows, and AI limitations.
This builder-first role works directly with founders to build Sainapse's customer-acquisition system using agents, data, code, and experiments, with qualified enterprise demos as the north-star metric. Responsibilities include building an empirical ideal-customer-profile system, personalized messaging and booking workflows, and running experiments across outbound, search, content, and paid channels. Requires evidence of creating pipeline or revenue, ability to build systems using agents and APIs, and experimental judgment.
