Senior Forward Deployed AI Engineer

Location: Remote, US
Travel: Up to 25% for customer engagements

About the Role

We are seeking a Senior Forward Deployed AI Engineer to work directly with strategic enterprise customers to design, build, and deploy high-impact AI solutions.

This is a highly hands-on role combining software engineering, AI/ML, solution architecture, and customer engagement. You will take ownership of the full solution lifecycle—from understanding complex business problems and rapidly prototyping solutions through production deployment, optimization, and knowledge transfer.

You will work at the intersection of AI engineering and enterprise transformation, partnering closely with business and technical stakeholders to turn ambiguous challenges into scalable, production-ready solutions.

What You’ll Do

• Work directly with enterprise customers to understand business challenges, data landscapes, and AI opportunities.
• Design and deliver agentic AI workflows, RAG applications, knowledge graphs, and intelligent decision-support solutions.
• Rapidly prototype and develop POCs that demonstrate measurable business value.
• Own solutions end-to-end across discovery, architecture, development, deployment, and optimization.
• Build enterprise AI applications across private cloud, GPU, and modern data platforms.
• Integrate AI solutions with enterprise systems including ERP, CRM, data warehouses, data lakes, and streaming platforms.
• Build scalable pipelines across structured and unstructured data.
• Develop LLM/SLM applications using technologies such as RAG, vector databases, LlamaIndex, Haystack, LangChain, LangGraph, and CrewAI.
• Develop production applications using Python, Node.js/Go, React/Vue, SQL/NoSQL, Docker, Kubernetes, and CI/CD.
• Implement monitoring, observability, telemetry, security, and governance for production AI systems.
• Identify new AI opportunities and help customers expand successful solutions into additional business areas.
• Create reusable architectures, accelerators, frameworks, and engineering patterns.
• Share field insights with internal product and engineering teams to influence future capabilities.
• Mentor engineers and customer teams and support knowledge transfer.

What We’re Looking For

• 10+ years of experience across software engineering, data engineering, AI/ML, or related disciplines.
• 4+ years in customer-facing, consulting, solutions engineering, or forward-deployed roles.
• Palantir certification required.
• Strong hands-on experience with Palantir Foundry and/or AIP, including ontology-driven solutions.
• Proven experience taking AI/ML solutions from prototype through production in enterprise environments.
• Advanced Python development skills, alongside experience with Node.js and/or Go.
• Strong experience with React/Vue, SQL/NoSQL databases, APIs, and modern application development.
• Practical experience with LLMs, prompt engineering, RAG, vector databases, AI agents, and agent orchestration.
• Experience with frameworks such as LangChain, LangGraph, CrewAI, LlamaIndex, or Haystack.
• Strong DevOps and cloud-native experience, including Docker, Kubernetes, CI/CD, and GPU infrastructure.
• Experience integrating disparate enterprise systems, data platforms, and APIs.
• Ability to take an ambiguous business problem and independently translate it into a technical solution.
• Excellent communication skills, with the ability to engage equally well with executive stakeholders, business users, architects, and engineers.
• Experience with AI evaluation, model optimization, fine-tuning, distillation, or related techniques is highly desirable.
• Experience designing multi-agent systems, tool-use workflows, and autonomous AI applications.
• Familiarity with enterprise GPU infrastructure and private cloud environments.
• Background in technology consulting, AI startups, Forward Deployed Engineering, or Solutions Engineering.

Preferred Experience

Experience in one or more of the following domains is advantageous:

• Financial Services
• Healthcare
• Supply Chain & Manufacturing
• Defense
• Energy

Additional experience with knowledge graphs, semantic modeling, ontology development, MCP, document intelligence, or ontology-driven data management would be highly valuable.

The Ideal Candidate

The ideal candidate is an engineer first who is comfortable operating directly with customers. You enjoy taking a loosely defined problem, understanding the underlying business need, building something quickly, and then turning that prototype into a reliable production solution.

You should be comfortable working in fast-moving, ambiguous environments, making technical decisions independently, and communicating complex AI concepts to both technical and non-technical audiences.

This is an opportunity to have significant ownership and customer impact while working on some of the most advanced enterprise AI and agentic AI use cases in the market.