Forward Deployed Engineer – Agentic

About the Job

Job Description: Senior Forward DeployedEngineer (AI/ML)

About the Role

We're seeking a Senior Forward Deployed Engineer who has evolvedfrom traditional ML engineering into the modern AI stack, bringing a consultingmindset to customer-facing delivery. You'll embed with clients to design,build, and ship production AI systems—translating ambiguous business problemsinto deployed solutions.

What You'll Do

• Embed directly with client teams to scope, prototype, and deploy AI-powered applications end-to-end
• Architect solutions using modern LLM tooling (agentic frameworks, RAG pipelines, orchestration layers) while applying rigorous ML fundamentals where they still matter
• Translate business requirements into technical roadmaps, then personally build the systems that deliver them
• Own the full lifecycle: discovery, POC, production hardening, evaluation, and handoff
• Serve as the technical bridge between client stakeholders and internal product/engineering teams
• Mentor client and pod engineers on AI-native development practices

What We're Looking For

Core background

• 8+ years hands-on engineering, with demonstrated transition from classical ML (feature engineering, model training, MLOps) to the modern generative AI stack
• Prior consulting or client-facing delivery experience, comfortable with ambiguity, shifting scope, and stakeholder management
• Strong software engineering fundamentals (production Python, APIs, cloud deployment)

Traditional ML foundation

• Experience building and deploying supervised/unsupervised models, feature pipelines, and evaluation frameworks
• Understanding of when classical approaches outperform LLMs (and the judgment to choose correctly)

Modern AI stack

• Hands-on experience with LLM application development: prompt engineering, RAG, agentic workflows, tool use, and function calling
• Familiarity with orchestration frameworks (LangChain, LlamaIndex, or equivalent), vector stores, and evaluation/observability tooling
• Experience shipping LLM systems to production, including latency, cost, and reliability tradeoffs

Consulting DNA

• Excellent written and verbal communication; can present to both engineers and executives
• Self-directed, able to lead engagements with minimal oversight
• Bias toward shipping working software over polished slides

What Success Looks Like

Within 6 months, you've independently led at least two clientengagements from discovery to production deployment, established repeatabledelivery patterns, and become a trusted technical advisor to client leadership.