AI Solutions lead
$141k - $307kLam Research
The group you'll be a part of The Office of the CTO is where innovation takes center stage. We inspire our global technical community to take on grand challenges, understand emerging trends, identify the critical inflections, and drive our sustainability, Environment, Social, and Governance (ESG) practices that will define the next generation of semiconductors and continued impact. The impact you'll make Join Lam as a Data Scientist, where you'll design, develop, and program methods to analyze unstructured and diverse big data into actionable insights. You'll develop algorithms and automated processes to evaluate large data sets from disparate sources. Your expertise in generating, interpreting, and communicating actionable insights enables Lam to make informed and data-driven decisions. What you'll do
- Design end-to-end AI solutions on Lam's shared AI platform - AI Foundry, Agent Runtime & Orchestration, Knowledge Service, and Ontology - grounded in enterprise data.
- Translate business problems into reusable solution patterns that delivery teams can adopt across R&D and enterprise use cases.
- Serve as the technical bridge between Platforms & Technology and the AI Delivery Execution and AI Product Management teams, ensuring platform capabilities are applied consistently.
- Lead solution and design reviews, and define and enforce architectural standards for agentic, RAG, and orchestration-based solutions.
- Embed security, governance, compliance, and cost-efficiency into solution designs by default, reducing IP and data-access risk across the enterprise.
- Champion reuse of common platform primitives over duplicated point solutions, driving interoperability and lowering total cost of ownership.
- Partner with product managers, AI governance, and engineering teams to take solutions from architecture through production deployment.
- Bachelor's or Master's in Computer Science, Engineering, or a related field, with 10+ years of AI engineering experience, including significant time as a hands-on solution or enterprise architect.
- Proven experience architecting enterprise-scale AI/GenAI solutions - including agentic frameworks, retrieval-augmented generation (RAG), and orchestration - as reusable, interoperable patterns.
- Deep knowledge of GenAI orchestration frameworks (e.g., LangChain, LangGraph) and agent communication standards (e.g., MCP).
- Solid understanding of various ML and DL frameworks and In-depth understanding of machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and their real-world advantages/drawbacks
- Demonstrated expertise with Transformer architectures - including attention mechanisms, encoder-decoder designs, and fine-tuning foundational models for NLP, CV, or multi-modal tasks.
- Hands-on experience building and optimizing Transformer-based systems, including RAG pipelines, embedding models, vector databases, and efficient inference techniques.
- Demonstrated ability to act as a single technical authority - leading design reviews, resolving cross-team architectural trade-offs, and influencing without direct authority.
- Strong grasp of security, governance, and compliance considerations for AI systems operating on enterprise and R&D data.
- Experience with knowledge/ontology services, semantic layers, and enterprise data foundations.
- Experience developing AI solutions on cloud platforms such as Azure and/or Databricks.
- Familiarity with full-stack software or data science development
- Strong communication skills, able to convey decisions to both technical and business audiences.
Vacancy posted 3 hours ago
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