Forward Deployed Engineer – Agentic

Job Description: Senior Forward Deployed Engineer (AI/ML)

About the Role

We're seeking a Senior Forward Deployed Engineer who has evolved from traditional ML engineering into the modern AI stack, bringing a consulting mindset to customer-facing delivery. You'll embed with clients to design, build, and ship production AI systems—translating ambiguous business problems into 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 client engagements from discovery to production deployment, established repeatable delivery patterns, and become a trusted technical advisor to client leadership.