Senior Forward Deployed Engineer (Agentic AI, RAG, Enterprise Architecture)

A fast-growing enterprise AI company is looking for a Senior Forward Deployed Engineer to take technical ownership of strategic AI solution deployments for enterprise customers. This role combines hands-on engineering, solution architecture, customer partnership, and delivery leadership, with a focus on building customer-specific applications on an Agentic AI platform.

This role is remote (US-based) with up to 25% travel for customer engagements.

You will lead the architecture, prototyping, implementation, and post-deployment optimization of large-scale Agentic and Knowledge AI solutions. The role involves working across enterprise data pipelines, multi-agent orchestration, RAG workflows, SLM fine-tuning, platform customization, full-stack delivery, and production-grade AI systems. You will collaborate closely with customers, Product, Platform Engineering, and cross-functional teams to translate ambiguous business needs into scalable engineering plans and successful deployments.

Required Skills

• 6–10+ years of engineering experience, including at least 2 years in customer-facing, field engineering, solutions engineering, or forward deployed engineering roles

• Proven experience building and deploying AI/ML, data-intensive, or enterprise-grade applications in production

• Strong full-stack development experience with Python, Node.js or Go, and React or Vue

• DevOps experience with Docker, Kubernetes, CI/CD, and modern cloud-based deployment practices

• Experience designing and implementing enterprise data pipelines and system integrations

• Strong knowledge of REST APIs, Python, SQL, GraphQL, Webhooks, and enterprise integration patterns

• Solid understanding of LLMs, prompt engineering, prompt tuning, vector databases, RAG pipelines, and agentic workflows

• Experience with vector databases such as AstraDB, Pinecone, or Weaviate

• Familiarity with RAG frameworks such as LlamaIndex or Haystack

• Experience with agent and workflow orchestration tools such as LangChain, LangGraph, or CrewAI

• Ability to lead technical solution design and implementation for strategic enterprise customers

• Experience customizing platform components, integrating APIs, building reusable tooling, or extending platform logic

• Strong understanding of observability, monitoring, versioning, telemetry, and trustworthy AI deployment practices

• Ability to translate ambiguous customer needs into clear, actionable engineering plans

• Strong project ownership, mentoring, communication, and collaboration skills across technical and business stakeholders

• Undergraduate degree, master’s degree, or PhD in Computer Science, Data Science, or a related technical field

Bonus Skills

• Knowledge of SLM fine-tuning, model distillation, and model optimization techniques

• Experience building and delivering enterprise Agentic AI solutions

• Experience working with Agentic development platforms

• Familiarity with graph databases, multimodal AI systems, evaluation frameworks, security, guardrails, and GPU infrastructure trends

• Experience contributing to reusable assets, technical best practices, internal frameworks, and documentation

• Prior experience supporting post-deployment optimization and production adoption for enterprise customers

• Experience partnering with Product and Platform Engineering teams to identify feature gaps, customer pain points, and product improvement opportunities