Responsible for technically reviewing and mentoring junior engineers with the object to deliver high quality software on time
Interact with peers across teams to carry out day to day activities
Initiates and drives continuous improvement projects aimed at improving productivity enabling business units deliver products with minimum cost and shortest cycle time
Drives productivity of the group by monitoring and reporting KPIs and driving necessary actions to address any gaps
Lead the identification, development, and responsible deployment of AI-enabled solutions for software engineering productivity, semiconductor equipment diagnostics by driving AI-assisted engineering practices, collaborating across software, process, hardware, field and support teams, and ensuring measurable quality, reliability and safe fallback behaviour
Who we’re looking for
Minimum Qualifications
Bachelor’s degree or master’s degree in engineering preferably Computer Sc / Electronics / Information Technology Years of Experience – 5 to 8 years
Mandatory Skills
Programming knowledge in C – preferably in hardware interfacing
Knowledge of RTOS
Experience in SDLC – Participated in design, IM and testing of projects
Strong analytical, logical, trouble shooting skills
Excellent problem solving and decision-making skills
Hands on experience in complete project development life cycle
Exposure to customer management
Hands-on experience applying AI-assisted software engineering tools for code generation, code review, Unit test creation, defect analysis, and technical documentation, with strong validation and secure-use practices
Ability to identify and deliver AI-enabled productivity solutions while protecting intellectual property, safety and regulatory compliance
Desirable Skills
Knowledge of OOPS concepts, Scripting
Experience in the semiconductor equipment manufacturing industry
Understanding of distributed systems and socket programming
Excellent communication and Presentation skills
Experience using equipment, sensor, alarm, trace, or log data for anomaly detection, predictive diagnostics, root-cause analysis, process monitoring, or maintenance optimization in semiconductor manufacturing systems
Familiarity with generative AI patterns and agentic workflows for engineering knowledge retrieval.
Exposure to deploying and monitoring AI solutions in production, including version control and lifecycle governance
Our commitment
We 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.
Lam 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.
Lam 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.
