{"id":2723856,"url":"https://alion.io/job/caterpillar-manager-engineering-4","title":"Manager Engineering","company":{"id":176554,"name":"Caterpillar","domain":"caterpillar.com","url":"https://alion.io/company/caterpillar","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Workday","truth_index":{"grade":"B","score":84,"open_postings":32,"ghost_share":0,"stale_share":0.844,"repost_share":0,"time_to_fill_p50_days":12,"computed_at":"2026-10-16T05:45:00Z"}},"role":"Management","role_family":"Management","seniority":"lead","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Chennai, India"],"countries":["IN"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":14000,"max_usd":36000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":28},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Agile","optional":false},{"name":"Machine Learning","optional":false}],"status":"live","first_seen_at":"2026-10-16T15:47:22Z","employer_posted_date":"2026-10-16","last_verified_at":"2026-10-17T01:25:44Z","board_verified":true,"closed_at":null,"days_open":0,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":0},"description":"Career Area:\nEngineeringJob Description:\nYour Work Shapes the World at Caterpillar Inc.\nWhen you join Caterpillar, you're joining a global team who cares not just about the work we do - but also about each other. We are the makers, problem solvers, and future world builders who are creating stronger, more sustainable communities. We don't just talk about progress and innovation here - we make it happen, with our customers, where we work and live. Together, we are building a better world, so we can all enjoy living in it.\nRole Definition\nThe Engineering Manager - Data Science is responsible for leading, coaching, and developing multiple pods of data scientists and machine learning engineers while ensuring high-quality, timely delivery of data science products and platforms. This role partners closely with AI product owners, AI architects, platform teams, and business stakeholders to ensure data science solutions are technically sound, scalable, and aligned to strategic outcomes.\nResponsibilities\nPeople Leadership & Talent Development\nLead, coach, and develop a team of data scientists and ML engineers\nSet clear performance expectations and support career development\nFoster an inclusive, high-performing team culture\nTechnical & Engineering Leadership\nProvide technical guidance across data science and ML solutions working closely with AI Architects\nEnsure adherence to engineering standards and MLOps practices\nReview model designs and deployment strategies\nDelivery & Execution Management\nOwn delivery execution and capacity planning\nEnsure predictable, high-quality delivery\nManage risks, dependencies, and technical debt\nStakeholder Collaboration\nPartner with AI Product Owners and business stakeholders\nCommunicate progress, risks, and outcomes clearly\nQuality, Governance & Responsible AI\nEnsure solutions meet quality, security, and compliance standards\nUphold responsible AI principles\nDegree Requirement\nBachelor’s degree in engineering, computer science, data science, or a related field (or equivalent practical experience). Post Graduate or higher is desired.\nSkill Descriptors\nEngineering Management\nDemonstrated ability to lead and develop high-performing technical teams delivering complex data science and machine learning solutions. Provides clear direction, sets expectations, and holds teams accountable for outcomes while supporting individual growth and engagement. Balances people leadership, technical oversight, and delivery execution in a fast-moving environment.\nData Science & Machine Learning\nStrong working knowledge of data science, machine learning, GenAI and statistical modeling concepts, including supervised and unsupervised learning, feature engineering, model evaluation, and experimentation. Able to guide and review technical approaches, challenge assumptions, and ensure solutions are fit for purpose without requiring hands-on model development as a primary responsibility.\nDelivery & Execution\nProven ability to plan, prioritize, and execute work in Agile or hybrid delivery environments. Manages team capacity, dependencies, and risks to ensure predictable delivery of high-quality outcomes. Uses data and metrics to assess progress, identify issues early, and drive continuous improvement.\nCommunication & Collaboration\nExcellent verbal and written communication skills, with the ability to clearly articulate complex technical concepts to non-technical audiences. Builds strong partnerships with product owners, architects, platform teams, and business stakeholders to align expectations, manage trade-offs, and deliver value.\nSoftware Development Life Cycle\nDemonstrated knowledge of software and data science development life cycles, including experimentation, prototyping, production deployment, and ongoing operations. Understands the differences between research-oriented work and production-grade solutions and guides teams accordingly.\nWorks within formal delivery and governance methodologies\nUnderstands phases, activities, dependencies, and key decision points across the life cycle\nIdentifies common risks and quality considerations at each stage\nInterprets and guides technical documentation, design artifacts, and delivery plans\nArtificial Intelligence\nWorking knowledge of artificial intelligence, GenAI and machine learning concepts, risks, and opportunities, with the ability to guide teams toward solutions that deliver business outcomes responsibly.\nUnderstands AI methodologies, capabilities, and limitations\nGuides teams in applying responsible AI principles, including fairness, transparency, robustness, and governance\nKeeps informed of emerging AI technologies and evaluates their applicability to business needs\nSupports the adoption of AI practices that balance innovation with risk management\nProgramming & Technical Literacy\nStrong technical literacy across programming and data science tools sufficient to effectively review code, designs, and technical approaches.\nAble to assess code quality, maintainability, and architectural alignment\nCollaborates effectively with hands-on engineers and data scientists\nUnderstands testing, version control, and deployment concepts\nHands-on coding is not a primary responsibility, but technical depth is sufficient to guide and challenge solutions\nTechnical Troubleshooting\nDemonstrated ability to lead teams through complex technical and operational issues across data, models, and production systems.\nGuides investigation and resolution of data, model, and system issues\nReviews logs, metrics, and system behavior to support root cause analysis\nPartners with platform and operations teams to resolve production incidents\nEnsures issues are documented, learnings are captured, and preventative actions are implemented\nNote\nThis Job Description is intended as a general guide to the job duties for this position and is intended for the purpose of establishing the specific salary grade. It is not designed to contain or be interpreted as an exhaustive summary of all responsibilities, duties, and effort required of employees assigned to this job. At the discretion of management, this description may be changed at any time to address the evolving needs of the organization. It is expressly not intended to be a comprehensive list of “essential job functions” as that term is defined by the Americans with Disabilities Act.\nPosting Dates:\nOctober 16, 2026 - October 29, 2026Caterpillar is an Equal Opportunity Employer. Qualified applicants of any age are encouraged to apply\nNot ready to apply? 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