Forward Deployed Engineer, Enterprise

Role overview Embed directly with enterprise customers as the technical owner across the lifecycle of strategic AI deployments, from discovery through production rollout. This full-time, on-site role in New York partners deeply with customer engineering, data, and product teams to build production-grade RAG pipelines, agent workflows, and custom integrations while feeding field insight back into product and engineering.

Responsibilities - Lead technical discovery and solution design during pre-sales and expansion conversations with enterprise accounts - Scope, build, and deliver proofs of concept that demonstrate clear business and technical value - Design and implement production-ready integrations including RAG pipelines, agent workflows, internal tools, and industry-specific GenAI applications - Partner with customer engineering, data, product, and AI teams to move use cases from prototype to production - Monitor customer API usage patterns and recommend improvements to reliability, latency, and coverage - Translate recurring customer needs and technical patterns into product and roadmap input - Create reusable enterprise assets such as reference architectures, integration templates, deployment guides, and demo environments - Represent the company in customer architecture reviews, executive technical conversations, and post-deployment reviews

Requirements - Five or more years of software engineering experience, ideally in a customer-facing role such as Forward Deployed Engineer, Solutions Architect, or Sales Engineer - Strong hands-on engineering ability with Python, APIs, backend systems, and production software development - Experience building with LLMs, Retrieval-Augmented Generation, agent architectures, context engineering, and modern AI application stacks - Track record working with enterprise customers on technical discovery, POCs, solution design, stakeholder management, and production rollout - Understanding of how enterprises evaluate, deploy, secure, and scale AI systems - Clear communication skills with both technical and executive stakeholders - High autonomy, strong ownership, and comfort in a fast-moving startup environment - Based in New York City or willing to relocate

Nice to have - Experience with agent or LLM orchestration frameworks such as LangChain, LlamaIndex, LangGraph, OpenAI Agents SDK, or CrewAI - Familiarity with vector databases such as Pinecone, Weaviate, pgvector, or Qdrant - Domain experience in financial services, legal, consulting, enterprise SaaS, or knowledge management - Prior work at a high-growth AI infrastructure, developer tools, or enterprise SaaS company - Experience building internal tools, technical playbooks, demos, or reusable customer-facing assets