AI Technical Innovation Lead

This is a hands‑on role for an exceptional technologist with deep AI expertise, a strong passion for AI, and validated software and applied AI engineering skills, translating emerging capabilities and research into scalable, production‑ready AI solutions for Arm.

Working across AI Enablement, Delivery, Data, Architecture, Engineering, IT, Compliance, Security, and business teams, this role will shape Arm’s AI roadmap, lead experimentation and incubation, and turn ideas into reusable patterns, internal products, and measurable business outcomes. It will primarily support the core AI roadmap and key transformation initiatives across Arm.

• Bring deep expertise across AI, ML, GenAI, LLMs, RAG, agentic systems, and applied AI engineering to help shape practical, reusable AI capabilities at Arm.
• Define and embed AI engineering standards for evaluation, observability, testing, governance, and operational readiness so solutions are reliable, secure, and ready for use.
• Apply strong software engineering practices to architect, build, deploy, and scale end-to-end products, APIs, services, internal tools, and enterprise applications.
• Design, build, test, and scale AI concepts, internal products, mini apps, and reusable enterprise solutions across AI workflows, API and MCP style integrations, AI coding assistants, and agentic use cases.
• Contribute to Arm’s emerging technical AI roadmap by assessing models, frameworks, whitepapers, open-source projects, and ecosystem shifts, including areas beyond standard enterprise AI.
• Lead AI experimentation and incubation, testing new ideas and turning the most promising into proofs of value, MVPs, and production solutions with clear business outcomes.
• Create and evolve reusable patterns, frameworks, and guardrails, working with teams across Arm to enable responsible innovation across Arm’s engineering communities.
• Identify and reduce risks such as hallucination, prompt injection, data leakage, bias, and unsafe tool use.
• Collaborate closely with Engineering IT to develop agentic and AI solutions that improve the engineering experience and developer productivity.

• Deep hands on expertise across AI, ML, GenAI, LLMs, RAG, reinforcement learning, agentic and multi-agent systems, and applied AI engineering.
• Strong software and backend engineering capability, with experience architecting, building, testing, deploying, and scaling AI‑enabled products, APIs, services, microservices, and enterprise solutions, grounded in solid system design, integration, data, CI/CD, observability, security, and cloud‑native practices.
• Strong Python skills and experience with frameworks such as PyTorch, Tensor Flow, scikit-learn, Lang Chain, Lang Graph, or similar.
• Experience with LLM and agentic patterns, including retrieval, orchestration, tool use, evaluation, guardrails, and governed production deployment.
• Solid understanding of AI architecture, cloud platforms, APIs, model‑agnostic design, reusable frameworks, and scalable AI engineering practices.
• Demonstrated ability to turn emerging research, whitepapers, open‑source developments, and new tools into practical, high‑value solutions, moving from concept to MVP and production while balancing speed, engineering quality, and business impact.
• Solid grasp of responsible AI, privacy, governance, model security, risk management, vector databases, retrieval systems, and observability/evals.

• Effectively engaged in applied AI research, emerging technologies and open source ecosystems. Familiarity with robotics, edge AI applications beyond typical enterprise use cases.
• Knowledgeable in AI for sustainability, including energy-efficient architectures and green compute!

Joi…