Senior Forward Deployed Engineer, Agentic AI

Robots and Pencils•Seattle, WA

36d•Onsite

About The Position

Robots & Pencils is seeking an outcome oriented Forward Deployed Senior Software Engineer to partner with strategic clients on high-impact agentic AI applications. You'll embed directly with customers throughout the product lifecycle, working hands-on from design to production. As an FDSE, you'll serve as technical thought partner, actively coding and leveraging your software engineering experience across application ideation, development, delivery, and scaling. You'll work on-site with clients, driving outcomes that maximize their business value.

Requirements

Bachelor’s degree in Computer Science, Engineering, or equivalent experience.
7+ years of professional software development with significant ownership of architecture and delivery.
3+ years of Python in ML/AI systems, including PyTorch or TensorFlow.
1+ years building with Generative AI: LLM agents, prompt engineering, LangGraph, LangChain
Hands-on RAG experience - semantic chunking, metadata enrichment, embeddings, retrieval quality, and latency/cost tuning.
Experience with vector stores such as pgvector, Weaviate, or Chroma.
Understanding of modern AI interoperability standards such as MCP (Model Context Protocol) and AI communication standards.
Strong cloud and IaC (Terraform, CloudFormation) background - AWS, Azure, or GCP - plus containerization and distributed systems fundamentals.
Strong AWS expertise: services, solid grasp of compute, networking, storage, security, and container platforms.
Solid SDLC practices - testing strategies, CI/CD, code reviews, observability, and incident management.
Upper-intermediate English for client communication.
Experience leading complex technical projects with multiple stakeholders.
Strong communication skills for technical and executive audiences.
Ability to context-switch and adapt to diverse client environments.
Willingness to travel to client sites.

Nice To Haves

Knowledge of advanced RAG patterns - Adaptive RAG, Agentic RAG, Self-RAG - and retrieval evaluation methods.
Experience building agentic applications with LangGraph, LangChain, or AutoGen, familiarity with patterns and techniques such as ReAct (Reason + Act), Chain-of-Thought, Tree-of-Thoughts.
MLOps/AIOps exposure - model deployment, lifecycle, governance, safety, red-teaming, data/privacy controls, prompt/version management, offline and online evals using managed services and/or Docker/Kubernetes with MLOps best practices.
Experience with LLM fine-tuning techniques - SFT, RLHF, DPO, PEFT, LoRA/QLoRA - on hyperscalers’ platforms like AWS SageMaker, Google Vertex AI, or Azure ML.
Experience with production support and/or deployment on AWS, Azure, or GCP using modern CI/CD.
Prior consulting or professional services experience.

Responsibilities

Embed with strategic clients as their technical partner for agentic AI applications.
Build full-stack prototypes and production features using Python and JavaScript.
Evaluate and integrate LLMs and tooling for the task at hand - e.g., AWS Bedrock, Anthropic Claude, OpenAI GPT models, LangGraph/LangChain, retrieval and tool-use orchestration.
Architect RAG systems, agent workflows, and conversational interfaces tailored to client needs.
Own the path to production - CI/CD, IaC, observability, cost/performance tuning, SLIs/SLOs, and incident response.
Iterate rapidly based on client feedback and business requirements, translate business goals into technical plans that accelerate time to value.
Own end-to-end delivery from initial concept to production deployment
Identify opportunities to maximize client business value through agentic AI capabilities
Provide strategic guidance on application architecture and implementation approaches
Accelerate client time-to-value through hands-on development and knowledge transfer
Pick up missing knowledge and skills as needed to ensure project success
Lead complex, multi-stakeholder initiatives on-site and remotely; drive clarity, remove blockers, and keep execution on track.
Set coding standards and architecture patterns in the client codebase; write clear docs, RFCs, and runbooks.
Mentor client and partner engineers through reviews, pairing, and design sessions; raise the bar on quality and velocity.
Make sound tradeoffs under real-world constraints - privacy, compliance, data residency, cost, and security.
Align delivery with Robots & Pencils’ responsible AI practices and client governance.
Work with internal product, engineering, and customer success teams.
Share client insights to drive platform improvements and feature priorities.
Contribute reusable patterns, frameworks, and documentation back to core platform.
Collaborate across time zones with distributed teams.
Participate in pre-sales technical discussions and solution scoping.