We are seeking a senior, hands-on Full-Stack AI Tech Specialist to architect, build, and scale Lightspeed’s multi-agent AI platform. This is a deep technical individual contributor role for someone who operates seamlessly across the full stack, from agent orchestration and AI workflows to APIs, data access, and user experience, and helps define how conversational AI is delivered at enterprise scale. The role is designed for a builder who thrives at the intersection of data, AI, platform engineering, and developer experience, with end-to-end technical ownership and meaningful enterprise impact.

What You’ll Do

• Design and implement multi-agent AI systems using Google ADK, including agent orchestration, tool calling, memory, and reasoning workflows.
• Build end-to-end conversational AI experiences spanning frontend, backend services, data platforms, and AI/ML components.
• Develop reusable agent frameworks, APIs, and platform primitives that enable teams to rapidly build domain-specific AI agents.
• Integrate LLMs with enterprise data sources, ensuring secure access, policy enforcement, and governance-by-default.
• Implement human-in-the-loop patterns, evaluation loops, and guardrails for responsible AI behavior.
• Drive platform reliability, performance, observability, and cost efficiency for AI workloads.
• Act as a technical anchor for complex design decisions, proofs-of-concept, and production hardening.

• Partner with product, data science, and platform teams to translate AI use cases into scalable platform capabilities.

  Why This Role Matters

• You will help define how AI agents are built, governed, and scaled across Ford.
• You’ll work on a platform that directly shapes enterprise decision-making and productivity.
• This is a senior IC role with real architectural influence, not a people-management track.

What You Bring

• Deep, hands-on experience building production-grade AI systems, preferably involving conversational AI, agents, or LLM-based architectures.
• Strong full-stack engineering expertise across backend services, APIs, data access layers, and modern frontend frameworks.
• Practical experience with multi-agent frameworks, orchestration patterns, or Google ADK (or equivalent agent platforms).
• Solid understanding of the AI/ML lifecycle: prompt engineering, tool use, evaluation, monitoring, and continuous improvement.
• Experience building cloud-native systems using containers, Kubernetes, CI/CD, and infrastructure-as-code.
• Strong grounding in enterprise data platforms, security, access controls, and privacy-aware system design.

• A clear point of view on responsible AI, trust, and human-in-the-loop augmentation as non-negotiable.

  Representative Technologies

• Google ADK, LLM ecosystems, agent frameworks
• Python, Java, Springboot
• Modern frontend frameworks (React or equivalent)
• ML/AI tooling (LLMs, embeddings, vector stores, evaluation frameworks)
• Cloud platforms, Kubernetes, APIs, distributed data systems