Principal/Lead Forward Deployed Engineer (Agentic AI, RAG, Enterprise Architecture)

A fast-growing enterprise AI company is looking for a Principal/Lead Forward Deployed Engineer to own end-to-end Agentic AI solution design, development, delivery, and optimization for multiple strategic enterprise customers.  This role sits at the intersection of engineering, architecture, consulting, and customer partnership, with responsibility for shaping technical strategy, leading complex deployments, mentoring teams, and translating ambiguous business needs into scalable AI solutions. This role is remote (US-based) with up to 25% travel for customer engagements. You will architect and deliver robust Agentic AI systems across industries, working closely with senior customer stakeholders as well as internal Product, Platform Engineering, and Forward Deployed Engineering teams. The role requires deep technical expertise in RAG, multi-agent orchestration, retrieval optimization, SLM/LLM fine-tuning, enterprise integrations, observability, and auditable AI, along with the leadership ability to define standards, create reusable frameworks, and drive engineering excellence at scale. Required Skills

- 10+ years of relevant experience in enterprise technology, B2B software, AI consulting, or technology consulting

- Proven experience leading complex engineering engagements and customer-facing technical teams

- Strong background in Forward Deployed Engineering, Solutions Engineering, or similar client-facing engineering functions

- Deep expertise in AI solution architecture, including multi-agent systems, RAG, SLMs, LLMs, and multimodal AI

- Experience designing and delivering enterprise-grade AI solutions across multiple domains or industry verticals

- Strong understanding of enterprise integration patterns, data engineering, full-stack engineering, and cloud/devops environments

- Hands-on experience with SQL, Python, Go, Java, JavaScript, data engineering, vector databases, retrieval optimization, prompt engineering, and agentic system design

- Ability to own technical strategy, solution quality, architecture decisions, and delivery roadmaps for multiple enterprise deployments

- Experience setting engineering standards, creating reusable frameworks, and building scalable delivery playbooks

- Strong stakeholder management skills, with the ability to advise senior customer executives and internal leadership

- Excellent communication skills, with the ability to balance technical depth, business priorities, and customer outcomes

- BS, MS, or PhD in Computer Science, Data Science, or a related technical discipline Bonus Skills

- Advanced understanding of regulatory, compliance, security, and governance requirements for AI in enterprise environments

- Experience establishing engineering processes, quality standards, and best practices across distributed teams

- Published work, open-source contributions, or thought leadership in Agentic AI, OpenAI, LangChain, LangGraph, RAG, or Knowledge Graph communities

- Experience drafting technical best practices, playbooks, whitepapers, blog posts, or other thought leadership content

- Familiarity with GPU infrastructure trends, SLM/LLM fine-tuning, and large-scale AI platform optimization

- Experience representing a company at industry events, technical forums, or strategic partnership discussions

- Strong background in observability, monitoring, telemetry, and auditable AI systems