AI Technical Innovation Lead

In this hands-on role you will shape Arm's AI roadmap and lead experimentation to turn ideas into scalable, production-ready AI solutions. You’ll work across engineering, IT, security, and business teams to enable responsible AI at scale, building reusable patterns and internal products with measurable business impact. You will translate research into practical capabilities while embedding governance, observability, and security by design. This is an opportunity to influence enterprise AI transformation at a world-class technology company.

• hybrid working
• learning and professional growth
• inclusive environment
• collaboration with industry leaders
• equal opportunities

• Shape practical, reusable AI capabilities and contribute to Arm's emerging AI roadmap
• Define and embed AI engineering standards for evaluation, observability, testing, governance, and production readiness
• Architect, build, deploy, and scale AI-enabled products, APIs, services, and internal tools
• Design and scale AI concepts, mini apps, and reusable enterprise solutions across AI workflows and integrations
• Assess models, frameworks, whitepapers, and ecosystem shifts to inform strategy
• Lead AI experimentation and incubation, turning ideas into MVPs and production solutions with business value
• Create reusable patterns and guardrails to enable responsible innovation across engineering teams
• Identify and mitigate risks such as hallucination, prompt injection, data leakage, bias, and unsafe tool use
• Collaborate with Engineering IT to improve developer productivity through agentic and AI solutions

• Deep hands-on expertise across AI, ML, GenAI, LLMs, RAG, reinforcement learning, agentic and multi-agent systems
• Strong software/backend engineering with experience delivering AI-enabled products and enterprise solutions, grounded in system design, data, CI/CD, observability, security, and cloud-native practices
• Strong Python skills with PyTorch, TensorFlow, scikit-learn, LangChain, LangGraph, or similar
• Experience with LLM and agentic patterns: retrieval, orchestration, tool use, evaluation, guardrails, and production deployment
• Solid understanding of AI architecture, cloud platforms, APIs, model-agnostic design, and scalable engineering practices
• Ability to translate research and new tools into practical, high-value solutions from concept to MVP to production
• Solid grasp of responsible AI, privacy, governance, model security, risk management, vector databases, retrieval systems, and observability/evals

• cross-functional collaboration
• clear communication
• problem solving and analytical thinking
• Python
• PyTorch
• TensorFlow