Job description

Multi-Agent AI LLMs & Physical Operations Startup ABOUT OPERIO Operio.ai is building the next generation of AI-native operational intelligence for fleet and field service organizations. Our platform empowers dispatchers, fleet managers, and field teams with purpose-built AI assistants that turn complex operational data into instant, actionable insight. We are a small, fast-moving team headquartered in Palo Alto—founded by engineers and operators who have built and scaled enterprise software and AI systems. THE ROLE We are looking for a Senior Applied AI Engineer to be a core builder of the Operio AI platform. You will design and develop our multi-agent AI framework, own the architecture for LLM-powered features end to end, and work directly with the founding team to shape the technical direction of the product. This is a high-impact, hands-on role in a company where every engineer has outsized influence on both the technology and the product roadmap. This role is ideal for someone who thrives in ambiguity, ships quickly, iterates on real user feedback, and has strong opinions—loosely held—about how to build AI products that actually work in production. WHAT YOU'LL DO • Design and implement the Operio multi-agent framework, including agent orchestration, task decomposition, tool use, and memory systems • Build and optimize LLM-powered pipelines for text-to-SQL, natural language understanding, and structured data reasoning over fleet telemetry and operational data • Develop retrieval-augmented generation (RAG) and context-reduction strategies to maximize LLM accuracy and cost efficiency at scale • Architect and maintain prompt engineering systems, evaluation harnesses, and automated testing pipelines for AI features • Collaborate closely with product and design to translate complex AI capabilities into intuitive user-facing features • Instrument, monitor, and continuously improve model performance, latency, and reliability in production • Stay current with the rapidly evolving LLM ecosystem and bring new techniques and tools to the team proactively WHAT WE'RE LOOKING FOR Required • 4+ years of software engineering experience, with at least 2 years focused on applied machine learning or LLM-based systems • Demonstrated experience building multi-agent systems using frameworks such as LangGraph, LangChain, AutoGen, CrewAI, or equivalent • Strong proficiency in Python and production-grade ML/AI engineering practices (testing, observability, CI/CD) • Hands-on experience with LLM APIs (OpenAI, Anthropic, Gemini, etc.) and retrieval frameworks (vector stores, semantic search, hybrid retrieval) • Experience with text-to-SQL, structured query generation, or reasoning over relational/semi-structured data • Track record of delivering AI features in a fast-paced startup or equivalent high-velocity environment • BS degree or higher in Computer Science, Electrical Engineering, Applied Mathematics, or a closely related technical field Preferred • Experience with agentic AI platforms such as Claude Agents, OpenAI Assistants, or similar hosted frameworks • Familiarity with fleet management, telematics, IoT, or field service operations domains • Exposure to evaluation frameworks (RAGAS, LangSmith, PromptFlow, custom evals) for LLM quality and regression testing • Contributions to open-source AI/ML projects or publication of relevant technical work • Experience working across the full stack in early-stage companies (API design, data pipelines, lightweight front-end integration) • MS or PhD in a relevant AI/ML field is a plus, but not required OUR STACK • LLMs: Anthropic Claude, OpenAI GPT series, with model-agnostic abstraction layers • Orchestration: LangGraph / LangChain, custom agent frameworks • Data: PostgreSQL, dbt, Dagster, Samsara/Geotab/SkyBitz telematics integrations • Backend: Python (FastAPI, Django), REST and streaming APIs • Frontend: React / Next.js • Infrastructure: AWS, Docker WHAT WE OFFER • Competitive salary and meaningful early-stage equity • Full medical/dental/vision coverage for employees • 401k plan • Generous pre-IPO company equity • Opportunity to be a defining technical voice at a company building in a rapidly expanding market • Flexible hybrid work environment in Palo Alto, with autonomy over your tools and workflows

Requirements

Must-haves

Multi-Agent AI LLMs & Physical Operations Startup
This role is ideal for someone who thrives in ambiguity, ships quickly, iterates on real user feedback, and has strong opinions—loosely held—about how to build AI products that actually work in production.
Design and implement the Operio multi-agent framework, including agent orchestration, task decomposition, tool use, and memory systems
Build and optimize LLM-powered pipelines for text-to-SQL, natural language understanding, and structured data reasoning over fleet telemetry and operational data
Develop retrieval-augmented generation (RAG) and context-reduction strategies to maximize LLM accuracy and cost efficiency at scale
Architect and maintain prompt engineering systems, evaluation harnesses, and automated testing pipelines for AI features
Collaborate closely with product and design to translate complex AI capabilities into intuitive user-facing features
Instrument, monitor, and continuously improve model performance, latency, and reliability in production
Stay current with the rapidly evolving LLM ecosystem and bring new techniques and tools to the team proactively
4+ years of software engineering experience, with at least 2 years focused on applied machine learning or LLM-based systems
Demonstrated experience building multi-agent systems using frameworks such as LangGraph, LangChain, AutoGen, CrewAI, or equivalent
Strong proficiency in Python and production-grade ML/AI engineering practices (testing, observability, CI/CD)
Hands-on experience with LLM APIs (OpenAI, Anthropic, Gemini, etc.) and retrieval frameworks (vector stores, semantic search, hybrid retrieval)
Experience with text-to-SQL, structured query generation, or reasoning over relational/semi-structured data
Track record of delivering AI features in a fast-paced startup or equivalent high-velocity environment
BS degree or higher in Computer Science, Electrical Engineering, Applied Mathematics, or a closely related technical field
LLMs: Anthropic Claude, OpenAI GPT series, with model-agnostic abstraction layers
Orchestration: LangGraph / LangChain, custom agent frameworks

Nice-to-haves

Experience with agentic AI platforms such as Claude Agents, OpenAI Assistants, or similar hosted frameworks
Familiarity with fleet management, telematics, IoT, or field service operations domains
Exposure to evaluation frameworks (RAGAS, LangSmith, PromptFlow, custom evals) for LLM quality and regression testing
Contributions to open-source AI/ML projects or publication of relevant technical work
Experience working across the full stack in early-stage companies (API design, data pipelines, lightweight front-end integration)
MS or PhD in a relevant AI/ML field is a plus, but not required

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Effort: medium

Benefits

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Dental

Vision

401k