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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