{"id":178067,"url":"https://alion.io/job/lam-research-software-engineer-sys-5","title":"Software Engineer Sys 5","company":{"id":58649,"name":"Lam Research","domain":"lamresearch.com","url":"https://alion.io/company/lam-research","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Eightfold","truth_index":{"grade":"C","score":56,"open_postings":712,"ghost_share":0.442,"stale_share":0.046,"repost_share":0.737,"time_to_fill_p50_days":71,"computed_at":"2026-10-16T05:45:00Z"}},"role":"Backend","role_family":"Backend","seniority":"senior","employment_type":null,"work_mode":"hybrid","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Fremont, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":141000,"max":307000,"currency":"USD","period":"year","gross":null,"usd_annual":307000},"salary_estimate":null,"experience_years_min":7,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"Function Calling","optional":false},{"name":"LangGraph","optional":false},{"name":"LLM","optional":false},{"name":"LLM Guardrails","optional":false},{"name":"Model Context Protocol","optional":false},{"name":"Multi-Agent Systems","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"RAG","optional":false},{"name":"Structured Outputs","optional":false},{"name":"Tool Use","optional":false},{"name":"Fine-tuning","optional":true},{"name":"Human-in-the-Loop","optional":true},{"name":"LangChain","optional":true},{"name":"LangSmith","optional":true},{"name":"PEFT","optional":true},{"name":"Reinforcement Learning","optional":true},{"name":"RLAIF","optional":true},{"name":"RLHF","optional":true},{"name":"Synthetic Data","optional":true},{"name":"Tokenomics","optional":true},{"name":"Transformers","optional":true}],"status":"live","first_seen_at":"2026-07-01T06:54:39Z","employer_posted_date":"2026-07-06","last_verified_at":"2026-10-17T05:02:13Z","board_verified":true,"closed_at":null,"days_open":107,"trust":{"level":"ghost","repost_count":4,"flags":["repost"],"days_open":106},"description":"The group you’ll be a part of\nIn the Global Products Group, we are dedicated to excellence in the design and engineering of Lam's etch and deposition products. We drive innovation to ensure our cutting-edge solutions are helping to solve the biggest challenges in the semiconductor industry.\nThe impact you’ll make\nAs a Software Engineer at Lam, you will be at the forefront of innovation by designing, developing, and troubleshooting, and debugging software programs. Your role is pivotal in developing software tools that support design, infrastructure, and technology platforms. Your expertise will determine hardware compatibility and influence design, ensuring seamless integration between software and hardware.\nIn this role, you’ll make an impact across Lam’s entire product portfolio of equipment working within our centralized software engineering team, collaborating with some of the brightest minds in the industry.\nWhat you’ll do\nDesign and implement sophisticated architectural solutions for integrating LLM technology into business applications\nDevelop complex multi-step agentic pipelines around open- and closed-source LLMs.\nOwn infrastructure for model integration, routing, and evaluation.\nBuild MCP Servers - ensure model governance, versioning, access control, and monitoring for production AI systems.\nEvaluate, prototype, and integrate the latest advancements in AI and agentic systems as they emerge.\nCollaborate closely with cross-functional teams including business leaders, engineers, architects, and designers to align AI systems with business objectives.\nWho we’re looking for\nMinimum Qualifications:\n7+ years of shipping production software, with a strong track record of owning features end-to-end\nProven experience building AI agents, LLM-driven systems, or autonomous workflows with proper guardrails and evaluation mechanisms.\nHave practical AI systems experience with RAG, evals, monitoring, MCP/tool use, structured outputs, or multi-agent workflows\nProven experience with LLM orchestration patterns and frameworks (LangGraph, MCP, agent SDKs from major model providers).\nFoundational AI skills, including prompt engineering, model evaluation, agent orchestration, reasoning frameworks, and the ability to apply AI to improve engineering and operational outcomes.\nFamiliarity with context management, session state, or memory systems in AI or distributed systems. You’ve thought about what the model sees and why it matters.\nA systems-thinking mindset that connects AI models, data pipelines, and operational workflows end-to-end.\nStrong communication skills with the ability to influence senior engineers and product leaders.\nA passion for how AI can unlock potential to help our teams, our customers, and our communities achieve great things.\nPreferred qualifications\nPrior semiconductor equipment experience.\nFamiliarity with human-in-the-loop workflows, PEFT based fine-tuning, and LLM evaluation techniques.\nFamiliarity with AI safety, guardrails, monitoring, and responsible deployment practices\nProficiency with AI tracing and evaluation tools such as LangSmith to monitor hallucinations, latency, and tokenomics.\nUnderstanding of reinforcement learning, including RLHF, RLAIF, offline and online RL, safety-aware reward design, and feedback loops.\nExpertise in AI evaluation platforms, synthetic data generation, model-based judges, or red-teaming.\nExperience building and shipping multi-model AI systems in production.\nExperience operating in regulated environments. Solid grasp of security fundamentals - encryption, access controls, audit logging, secrets management.\nOur commitment\nWe believe it is important for every person to feel valued, included, and empowered to achieve their full potential. By bringing unique individuals and viewpoints together, we achieve extraordinary results.\nLam Research (\"Lam\" or the \"Company\") is an equal opportunity employer. Lam is committed to and reaffirms support of equal opportunity in employment and non-discrimination in employment policies, practices and procedures on the basis of race, religious creed, color, national origin, ancestry, physical disability, mental disability, medical condition, genetic information, marital status, sex (including pregnancy, childbirth and related medical conditions), gender, gender identity, gender expression, age, sexual orientation, or military and veteran status or any other category protected by applicable federal, state, or local laws. It is the Company's intention to comply with all applicable laws and regulations. Company policy prohibits unlawful discrimination against applicants or employees.\nLam offers a variety of work location models based on the needs of each role. Our hybrid roles combine the benefits of on-site collaboration with colleagues and the flexibility to work remotely and fall into two categories - On-site Flex and Virtual Flex. ‘On-site Flex’ you’ll work 3+ days per week on-site at a Lam or customer/supplier location, with the opportunity to work remotely for the balance of the week. ‘Virtual Flex’ you’ll work 1-2 days per week on-site at a Lam or customer/supplier location, and remotely the rest of the time.\nSalary\nCA San Francisco Bay Area Salary Range for this position: $141,000.00 - $307,000.00.\nThe above salary range for this position is relevant to applicants that reside or work onsite in the California, San Francisco Bay Area only. Salary offers will depend on factors that include the location you work from, your level, education, training, specific skills, years of experience and comparison to other employees already in this role. Actual salary may vary from salary offered due to numerous factors including but not limited to unpaid time off, unpaid leave, company mandated shutdown, and other relevant factors.\nOur Perks and Benefits\nAt Lam, our people make amazing things possible. 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