Principal AI Architect

Mainspring Energy•Menlo Park, CA

21h•Hybrid

About The Position

Mainspring Energy is evolving beyond using AI for simple productivity gains. We are seeking a Principal AI Architect to lead our transition into an organization where AI agents are fully embedded in our engineering development cycles. This is a strategic leadership role focused on architecting the future of how we build linear generator technology. At the principal level, you will not just support existing processes; you will define the AI strategy for engineering development workflows, ensuring that AI-driven automation has clear structure, rigorous guardrails, and measurable Return on Investment (ROI).

Requirements

12+ years of experience in software engineering or ML infrastructure, with a proven track record of moving AI beyond "chatbots" and into functional, automated workflows
Deep Expertise in Agentic Frameworks: Proven track record in building autonomous systems using the Gemini and Anthropic SDKs (specifically via Vertex AI). Expert-level proficiency in architecting agentic design patterns—including MCP (Model Context Protocol), multi-agent orchestration, and complex state management—within high-scale production environments
Strategic ROI Focus: Ability to bridge the gap between technical execution and business value, with experience presenting ROI cases to executive leadership
Security & Compliance Mindset: Expertise in building "safe-by-design" systems, specifically regarding data privacy and preventing model hallucinations in mission-critical engineering tasks

Responsibilities

Transition Mainspring from "AI-assisted" tasks to a model where autonomous and semi-autonomous AI agents are natively integrated into the engineering lifecycle—from code generation and hardware simulation to automated testing and documentation
Identify and re-engineer high-impact engineering bottlenecks, deploying AI agents that act as functional members of the development team
Establish a data-driven framework to measure the impact of AI on engineering velocity, error reduction, and resource optimization. You will be responsible for defining and reporting on clear ROI metrics for all AI initiatives
Design and implement automated guardrails within the CI/CD pipeline to ensure AI-generated output meets Mainspring’s rigorous safety, security, and quality standards
Establish governance frameworks for agentic behavior, including "human-in-the-loop" checkpoints, audit logs, and access controls to prevent drift or unauthorized actions in production environments
Build rigorous benchmarking systems to evaluate model reliability and cost-effectiveness, ensuring a lean and high-performing AI stack
Design the end-to-end infrastructure required to support multi-agent systems, including orchestration layers, long-term memory (Vector DBs), and tool-use capabilities (RAG)
Act as the technical authority on whether to leverage third-party AI platforms or develop proprietary agentic tools tailored to our specific hardware-software engineering needs