The Staff Software Engineer will be the primary architect and technical lead for the team building all AI agents across the ecosystem. Acting as a hands-on leader and Technical Lead, you will be responsible for the team's overall delivery, translating complex product requirements into actionable technical tasks for a small team. You will design and build high-stakes agentic architectures that power our multi-sided marketplace - including buyer and seller-side agents, platform onboarding assistants, and automated maintenance agents - while continuing to reason across multi-modal data sources like OEM manuals, parts catalogs, and repair history. You will remain deeply embedded in the codebase to solve the "grounding problem" where accuracy is non-negotiable.
Key Responsibilities
● Technical Execution: Lead the technical delivery by decomposing high-level roadmaps into granular, actionable tasks for the agent development team. You are the owner responsible for mentoring engineers and ensuring high-quality output through rigorous architectural oversight.
● Agentic Architecture Design: Architect and implement advanced agentic systems and RAG pipelines that perform multi-step reasoning across disparate data sources to answer complex diagnostic questions. This includes expanding beyond diagnostic systems to develop intelligent buyer/seller marketplace agents and platform agents that automate customer onboarding and ecosystem maintenance.
● Solving the Grounding Problem: Lead the development of confidence scoring systems and validation workflows to ensure "zero tolerance" for plausible-but-wrong AI output in heavy equipment service.
● Multimodal Agent Development: Design and code agents capable of processing and extracting procedures from diverse inputs, including text, images, and video, to generate verified training content.
● Customer AI Integration Strategy: Architect the APIs and data access patterns that allow customers to build their own AI solutions using our data while maintaining strict hallucination and scope controls.
● Production AI Scaling: Design and deploy production-grade AI capabilities within Google Cloud Platform and AWS, ensuring systems scale reliably with customer demand while managing compute costs effectively.
● Evaluation Frameworks: Establish the metrics and "gold dataset" pipelines needed to measure retrieval quality and improve agent accuracy over time
● AI Native SDLC: Actively utilize autonomous coding agents to plan, generate, and test AI logic, maintaining high velocity while ensuring code quality through agent-assisted peer reviews.
10 years of Software Engineering experience, with a proven history of shipping complex, distributed systems at scale.
Proven track record of designing and deploying agentic architectures, multi-step reasoning systems, and complex RAG pipelines in production.
Technical Stack: Expert mastery of Python (FastAPI, Django) and Agent development frameworks (eg, Google ADK)
AI & Retrieval Mastery: Deep experience in Agentic Architectures, GraphRAG, and multi-modal
agent design (processing images/video alongside text), Agent Evaluation.
MLOps frameworks (e.g., PyTorch, Scikit-learn, MLflow, Weights & Biases).
Cloud Infrastructure: Expertise in deploying AI workloads at scale across Google Cloud
Platform and AWS
Coding Agents: Demonstrated proficiency in using coding agents to accelerate the SDLC
and plan and code complex engineering tasks.
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