FDE (Forward Deployment Engineering)

We are seeking a Senior Forward Deployed Engineer (FDE) Lead specializing in Generative AI and Google Cloud Platform (Google Cloud Platform). In this high-impact, hybrid role, you will embed directly with enterprise customers to solve complex technical challenges at the intersection of production AI and enterprise infrastructure. You will act as the technical spearhead—translating ambiguous business requirements into scalable, production-ready LLM systems, custom RAG architecture, and fine-tuned model deployments built on Google Cloud Platform’s AI stack.

Key Responsibilities

·        Forward Deployed Engagement: Embed with client engineering and executive teams to scope, design, and deliver bespoke, high-value AI solutions directly in customer environments.

·        LLM Architecture & Delivery: Design and implement production-grade LLM workflows, agentic frameworks, retrieval-augmented generation (RAG) pipelines, and custom prompt/eval frameworks using Vertex AI, Gemini, and open-source ecosystems (LangChain, LlamaIndex, vLLM).

·        Enterprise Google Cloud Platform Foundation: Architect resilient cloud infrastructure to host, orchestrate, and secure AI systems, leveraging GKE, Cloud Run, BigQuery, Vector Search, and IAM.

·        Technical Leadership & Mentorship: Lead cross-functional pods of cloud and software engineers, enforcing best practices across code quality, LLM evaluation metrics, and enterprise CI/CD for AI/ML (MLOps).

·        Productionization & Optimization: Drive models from prototype to enterprise-grade production, optimizing for latency, throughput, token cost, groundings, and safety/guardrails.

·        Client Advisory: Partner with C-suite and product leadership to establish AI roadmaps, identify high-ROI enterprise use cases, and navigate cloud governance and data privacy requirements.

Qualifications & Requirements

·        Experience: 8+ years in software engineering, cloud architecture, or technical consulting, with at least 3+ years dedicated to building and deploying production AI/LLM applications and cloud solutions.

·        Google Cloud Platform & AI Stack: Hands-on mastery of Vertex AI, Gemini APIs, Vector Search, and core Google Cloud Platform infrastructure (Compute Engine, GKE, Cloud Functions, BigQuery).

·        LLM & Modern AI Tooling: Practical experience with embedding models, vector databases (Pinecone, Chroma, pgvector), agent frameworks, and LLM orchestration tools.

·        Programming & IaC: High fluency in Python and/or TypeScript, alongside infrastructure-as-code tools (Terraform).

·        MLOps & DevOps: Experience setting up CI/CD pipelines, containerized deployments (Docker, Kubernetes/GKE), model evaluation frameworks, and cost/latency monitoring for AI workloads.

·        Client-Facing Presence: Exceptional communication and consultative skills, with a demonstrated ability to operate in fast-paced, customer-facing environments.

Preferred Qualifications

·        Certifications: Google Cloud Professional Cloud Architect or Professional Machine Learning Engineer.

·        Advanced AI Expertise: Experience fine-tuning open-weights models (e.g., Llama, Gemma), implementing custom guardrails, or orchestrating multi-agent systems.

·        Pre-Sales / Technical Strategy: Proven background leading technical discovery workshops, building rapid Proof of Concepts (PoCs), and converting initial engagements into long-term enterprise partnerships.