Forward Deployed Engineer

*Forward Deployed Engineer – Agentic Transformation & AI-Native Portfolio Management* Want to make an application Make sure your CV is up to date, then read the following job specs carefully before applying. Role Overview: 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 xxoysbn 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. *Experience*: 10+ Years Note: This is a full-time position Location: Onsite (Client Location) Pay: $100,000.00 - $150,000.00 per year Experience: * Relevant: 7 years (Required) Willingness to travel: * 25% (Required) Work Location: In person