Mainspring Energy - Principal Software Architect
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 • What Principal Level Means at Mainspring • At principal level, you are the architect of the strategy, not just the executor. You are expected to define the technical roadmap that transforms our engineering culture, acting as a multiplier who elevates the entire organization's capability through AI. • $227,500 - $280,000 a year • This position is open to both onsite and remote candidates. The salary will be adjusted to reflect local market conditions based on employee location as well as the experience of the employee. Along with the base salary, Mainspring offers pre-IPO stock options + benefits.
Responsibilities
• AI Strategy for Engineering Workflows • Architect Embedded Agent Cycles: 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 • Workflow Optimization: Identify and re-engineer high-impact engineering bottlenecks, deploying AI agents that act as functional members of the development team • ROI & Performance Measurement: 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 • Governance, Guardrails, and Security • Standardized Guardrails: Design and implement automated guardrails within the CI/CD pipeline to ensure AI-generated output meets Mainspring’s rigorous safety, security, and quality standards • Responsible Agent Execution: 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 • Model Evaluation: Build rigorous benchmarking systems to evaluate model reliability and cost-effectiveness, ensuring a lean and high-performing AI stack • Technical Leadership & Infrastructure • Agentic Infrastructure: 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) • Build vs. Buy Strategy: 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
Benefits
• We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.
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