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Senior AI Engineer
Johnson ControlsCore Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in AI/ML architecture and technical strategy, with a strong focus on model selection, data architecture, and deployment in production environments. Proficient in Python, SQL, and deep learning frameworks, with experience in manufacturing and engineering contexts.
Highest-signal resume keywords
AI/ML System OwnershipPython ProgrammingSQL ProficiencyDeep Learning FrameworksManufacturing Intelligence
Tech Stack
Tools & technologiesAbout the role
Key responsibilities & impact- Set technical direction for AI/ML architecture and technical strategy across sales, engineering, and manufacturing systems
- Define model selection, data architecture, evaluation approach, deployment topology, and build-versus-buy recommendations
- Translate business problems into a prioritized portfolio of AI work with product management, sales operations, engineering leadership, and plant operations
- Establish standards for reproducible training and evaluation, model and prompt versioning, monitoring, drift detection, rollback paths, and audit trails
- Serve as senior technical voice in design reviews and mentor software and data engineers
- Extract structured requirements from customer specifications, mechanical schedules, submittal documents, PDFs, drawings, and spreadsheets
- Develop configuration and quoting assistance, competitive crossover matching, pricing and discount guidance, and cost estimation
- Build engineering automation for similar-order retrieval, BOM anomaly detection, configuration rule mining, conflict detection, and engineering change impact analysis
- Develop manufacturing intelligence for labor and routing prediction, material shortage and schedule risk forecasting, test-data anomaly detection, and quality defect prediction
- Apply computer vision for assembly verification, nameplate and label validation, or station completeness checks where appropriate
- Build retrieval-grounded assistants and agents that interact with configurator, PLM, and ERP APIs
- Design safe deployment with human-in-the-loop review, confidence thresholds, abstention, and traceability
- Define ground truth and continuously evaluate systems in production
- Address on-premise and edge inference, plant latency, intermittent connectivity, OT/IT segmentation, and cybersecurity constraints
- Establish AI data governance for customer, pricing, and design data, third-party model providers, retention, tenancy, and vendor terms
- Assess and improve data usability across CPQ, PLM, ERP, and MES systems
- Build pipelines, feature engineering, and datasets for repeatable AI development
- Partner with the Program Manager, who owns scope, schedule, and stakeholder accountability, while owning technical direction and feasibility
Requirements
What you’ll need- Bachelor's degree in Computer Science, Engineering, Applied Mathematics, Statistics, or a related field
- 5+ years in software or data engineering
- 5+ years building machine learning or AI systems that reached production and real users
- Demonstrated ownership of an AI/ML system in production over time, not proofs of concept
- Strong Python and SQL
- Experience with classical and tabular ML, including gradient boosting and scikit-learn
- Experience with deep learning frameworks
- Experience with LLM application patterns including retrieval, structured extraction, tool use, and evaluation
- Fluency with ERP and PLM schemas, MES and historian data, and semi-structured documents
- Experience deploying and operating models in production, including containerization, CI/CD, cloud ML platforms, monitoring, and cost management
- Candidates should be located within commuting distance of the facility or be open to relocating
- Preferred: Experience in manufacturing, industrial, or engineer-to-order environments
- Preferred: Familiarity with BOM structures, variant and option modeling, routings and standard times, and engineering change processes
- Preferred: Document AI and information extraction experience with engineering drawings, specifications, or technical documentation
- Preferred: Optimization and operations research exposure
- Preferred: Computer vision experience in an industrial setting
- Preferred: Edge or on-premise inference experience in an OT environment
- Preferred: Experience as one of the first senior AI hires, building the function rather than inheriting it
Benefits
Comp & perks- Competitive Bonus plan based on individual, group, and corporate performance
- Competitive benefits package
- Relocation assistance available
ATS Keywords
✓ Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Machine LearningData ArchitectureModel EvaluationComputer VisionFeature EngineeringContainerizationCI/CDCloud ML PlatformsGradient BoostingScikit-Learn
Soft Skills
MentoringTechnical LeadershipCollaboration
Tools & Technologies
ERP APIsPLM SystemsMES SystemsEngineering AutomationDocument AI
Industry Keywords
ManufacturingEngineer-to-OrderBOM StructuresOptimizationOperations Research