Senior AI Engineer
Job Overview The PE AI Transformation team is redefining how AI powers engineering at Arm! We partner with engineering teams across Arm to deliver real-world impact through applied AI—boosting productivity, fueling innovation, and making powerful AI tools part of every engineer’s workflow. Guided by our vision—engineering redefined through smarter workflows, faster execution, and greater creativity—we’re building systems that let technology amplify human potential. As an AI Engineer, you’ll be hands-on in designing, developing, and deploying AI capabilities that reshape how engineers work. You’ll learn from experienced AI architects and senior engineers, gaining exposure to sophisticated system design and scaling patterns, while supplying your own technical depth to deliver robust, high-quality solutions. You’ll also mentor junior peers and share practical insights gained through your work. Responsibilities
- Deliver end-to-end AI solutions, from proof-of-concept to production, that improve developer workflows and engineering productivity.
- Embed with partner teams to find opportunities, translate needs into AI solutions, and deliver tangible, measurable results.
- Implement and optimize LLM-based systems, including retrieval-augmented generation (RAG), evaluation, and guardrails.
- Build and refine agentic AI components such as planning, memory, and tool orchestration.
- Write production-ready, testable Python code, maintaining high standards for quality, security, and performance.
- Collaborate with and learn from senior engineers and architects, applying mentorship feedback to continuously improve design, code quality, and scalability awareness.
- Supply to shared components and documentation, helping establish reusable patterns and frameworks for future projects.
- Provide guidance to less-experienced team members, reviewing code and sharing knowledge through demos or pair programming.
- Stay ahead of emerging AI tools and frameworks, evaluating their potential to accelerate Arm’s engineering transformation.
- Experience in AI, ML, or software engineering, with validated delivery of production-grade solutions.
- Strong Python programming skills
- Experience deploying AI or ML models into production systems.
- Experience with LLM systems, including prompting, RAG, evaluation, and orchestration.
- Exposure to agentic AI frameworks (e.g., LangChain, LlamaIndex, or custom orchestration stacks).
- Familiarity with enterprise AI APIs (e.g., OpenAI, Anthropic, Azure OpenAI, or similar).
- Experience working with retrieval systems, prompt engineering, and cloud platforms (AWS, Azure, or GCP – AWS preferred).
- A learning-oriented mindset—open to feedback, eager to understand architectural trade-offs, and committed to refining your craft.
- Strong communication and collaboration skills, with the ability to partner effectively across disciplines.
- Experience in semiconductor or large-scale software environments.
- Familiarity with MLOps, data pipelines, or AI infrastructure.
- Contributions to open-source or technical communities.
- Experience using AI to improve developer workflows, code generation, or data visualization.