Ford Motor Company

Engineer

• Lead development testing across engine dynamometers, powertrain/hub dynamometers, and physical vehicles.
• Utilize virtual vehicle analytical simulations to front-load calibration development and demonstrate system capability.
• Conduct sensitivity studies to optimize the balance between emissions compliance, fuel economy, performance, and drivability.
• Synchronize the calibration of various sub-systems—including the engine, aftertreatment (TWC/GPF), transmission, and electric generator/motors—to ensure seamless integration and achievement of emissions targets.
• Utilize Design of Experiments (DOE) methods to efficiently map complex multi-variable calibration spaces and define robust operating strategies.
• Lead the setup and commissioning of prototype systems in both dyno and vehicle environments.
• Perform system-level debugging and troubleshoot complex mechanical, electrical, and software issues.
• Document and present calibration progress, trade-off results, and regulatory compliance status to program leadership and cross-functional teams.

Emissions Calibration Engineer

Analyst

• Act as the Jira back-end expert for the Unified Backlog. Manage user access, process flow, automations, and data integrity with efficiency. Document process flows and critical operations for both end-users and operations team members.
• Identify, design and recommend process improvements to streamline operations, enhance data quality, reduce costs, and increase productivity.
• Manage the Unified Backlog helpdesk, including reviewing requests, balancing workload to align and implement changes and efficiently track progress.
• Help drive the Unified Backlog's strategic direction, aligning with corporate objectives and initiatives. Analyze data to identify objective alignment, inefficiencies, and contribute to strategic planning.
• Define, track, and monitor KPIs and operational metrics to provide insights and measure progress towards team objectives.
• Engage with and advocate for Unified Backlog strategic priorities across engineering, product, and business. Collaborate with cross-functional teams to ensure alignment and effective communication.
• Manage topics in stakeholder forums, maintain clear communication, and present findings to leadership.

Feature Strategy Analyst

Full-stack Engineer

• Drive the usage of AI into every aspect of software to transform how we work
• Architect, develop and maintain solutions in Python
• Build and enhance front-end features using React and Angular
• Design and document robust AI solutions for the enterprise
• Deploy and operate applications on Google Cloud Platform (GKE, Cloud Functions, Cloud Storage, Pub/Sub, etc.)
• Champion and implement CI/CD pipelines automation, test automation, and trunk-based development
• Identify process gaps and lead initiatives to improve software delivery lifecycle (SDLC) maturity and make it easier to go from idea to deployed code
• Coach engineers on best practices: AI coding agents, TDD, observability, fault-tolerance
• Facilitate change management: introduce new practices and ensure smooth adoption
• Influence cross-functional stakeholders—Business, Product, Ops—to align on delivery goals
• Mentor teams: help them grow technical skills, soft skills, and take ownership of their work
• Understand how to effectively use engineering metrics; continuously refine key performance indicators

Senior Staff Software Engineer

• Lead the full lifecycle of PKI and Key Management API services supporting our vehicle products and ecosystem — lead customer requirements gathering, architecture design, implementation, testing, deployment, monitoring, and post-launch support.
• Design and develop RESTful APIs and web services that are robust, secure, and scalable for various features and use cases: CRL/OCSP, ACME, Certificate Issuance, message encryption/decryption, software signing, key rotation and certificate lifecycle management, HSM integration with PKCS11. Implement access control methods that enforce least privilege access principles using OAuth or mTLS.
• Implement and harden PKI and key services with deep knowledge of PKI industry standards, X.509, PKCS standards, elliptic curve cryptography (ECC) and RSA, post-quantum readiness, and hardware security module CSP integration. Apply hybrid encryption techniques with AES. Define and enforce PKI certificate policies and certificate profiles.
• Design fault-tolerant, highly available PKI services with zero-downtime issuance, disaster recovery, and multi-region replication.
• Release and Deploy your apps through build server, CI/CD pipeline, and infrastructure involving on-premises and cloud Kubernetes
• Monitor and address findings regularly in code base through SAST, DAST, software quality and security vulnerability scanning.
• Actively assist in monitoring our systems and performing root cause analysis to address issues quickly. Implement robust application logging and integration with Splunk and security monitoring systems.
• Define and lead best practices for our software development process, perform code reviews, and mentor engineers while remaining hands-on in the codebase.
• Working with ECU embedded development teams to understand embedded architecture requirements and the best approach of key management for each ECU.
• Authoring and managing technical cybersecurity requirements and process documentation.

Senior Software Engineer – PKI

• Lead and mentor a team of ABAP developers, providing technical guidance, code review, and ensuring adherence to coding standards and best practices.
• Oversee the design, development, and implementation of SAP Business solutions within S/4 HANA and SAP BTP.
• Define the SAP ABAP solution architecture for extensions and Integrations to Integrate SAP with various upstream and downstream systems.
• Participate in project planning, estimation, and risk assessment activities.
• Promote knowledge sharing and continuous improvement within the ABAP development team.
• Develop and maintain ABAP code within the S/4 HANA environment, utilizing modern ABAP techniques
• Design and implement custom solutions to meet specific business requirements, ensuring seamless integration with standard SAP functionality.
• Optimize ABAP code for performance, scalability, and maintainability.
• Leverage SAP BTP to develop and deploy cloud-native ABAP applications, utilizing the RAP and CAP programming models.
• Integrate SAP BTP applications with S/4 HANA and other SAP systems.
• Utilize SAP BTP Build to create user-friendly interfaces, workflows and Build process automation ( BPA / RPA) .
• Contribute to the architectural design of SAP solutions, ensuring alignment with business requirements and SAP best practices.
• Develop technical specifications and documentation for ABAP development projects.
• Evaluate new SAP technologies and provide recommendations for their adoption.
• Troubleshoot and resolve complex ABAP-related issues within the S/4 HANA and SAP BTP environments.
• Conduct root cause analysis and implement preventative measures to avoid future issues.
• Collaborate with other IT teams to resolve cross-functional issues.

SAP ABAP Technical Consultant

• Design Autonomous Loops: Transition from linear "chain" workflows to self-correcting agentic loops using frameworks like LangChain, LlamaIndex, or CrewAI.
• Tool-Use Architecture: Design and implement robust "tool-calling" capabilities, ensuring LLMs can reliably interact with external APIs and microservices.
• MCP Integration: Build and maintain Model Context Protocol (MCP) servers to bridge the gap between LLMs and our proprietary data silos securely and in real-time.
• High-Concurrency Back-end: Develop asynchronous Python (FastAPI) or Java services optimized for long-running AI tasks and token streaming.
• Streaming Front-end: Build responsive, stateful UIs in React or Angular that handle complex AI interactions (streaming text, generative UI components, and multi-modal feedback).
• Advanced RAG Pipelines: Go beyond basic vector search. Implement re-ranking, query transformation, and embedding optimization to maximize retrieval precision.
• Context Optimization: Master the "Context Window" by implementing prompt compression and "lost-in-the-middle" mitigation strategies.
• Evaluation & Observability: Establish AI Evals to quantify hallucination rates, latency, and cost. Lead the shift from "vibes-based" testing to rigorous, automated AI benchmarking.
• DevOps/MLOps: Manage CI/CD pipelines that include vector database migrations and automated prompt versioning.

Full Stack Software Engineer, AI Integration

• Ensure all machining processes meet or exceed safety, quality, and regulatory standards.
• Drive the APQP (Advanced Product Quality Planning) process and lead the development of PFMEAs to proactively mitigate risk.
• Champion quality resolution during new model launches, ensuring "Job 1" meets all specifications.
• Maintain a rigorous safety culture by monitoring construction and production areas for compliance.
• Partner with the Lead Engineer to manage critical launch milestones for new engine programs.
• Serve as the primary technical point of contact between OEMs, installation vendors, and plant operations.
• Develop and track detailed project plans, ensuring timelines and budgets stay on course.
• Design and implement cutting-edge manufacturing processes while optimizing existing lines for cost and efficiency.
• Oversee the design, installation, and runoff of new equipment, tooling, and fixtures.
• Collaborate with Product Development (PD) on Design for Manufacturing (DFM) to ensure new models are optimized for high-volume assembly.
• Act as a bridge between the plant team, OEMs, PD, and Tooling Engineers to ensure cross-functional alignment.
• Provide hands-on technical support to shop floor personnel and skilled trades to resolve complex equipment issues.
• Confidently communicate project status and technical challenges up the chain of command, translating shop-floor realities into executive-level insights.
• Utilize Six Sigma tools and data analytics to identify bottlenecks and reduce production costs.
• Apply Lean Manufacturing principles to streamline workflows and improve overall equipment effectiveness (OEE).
• Document and institutionalize "Lessons Learned" to ensure continuous improvement across future programs.

Manufacturing Engineer – New Program Launch

Product Manager

• Collaborate on multi-year product strategy for Ford Motor Company
• Own the strategy for your product area, defining your vision, goals, and investments
• Develop new product pitches and requirements, and translating into high quality product roadmaps
• Coordinating a diverse team of engineers, designers, and partner product teams to innovate new and enhance existing products to drive your vision.
• Managing a diverse roadmap and making tradeoff decisions between investments across multiple years
• Analyzing data and performing sophisticated analytical exercises
• Drive standardization, simplification, and automation of internal processes and product development mechanisms to increase throughput
• Managing weekly, and monthly product/business reporting

Product Manager – App Storefront

Systems Engineer

• Lead the definition and design of new emissions concepts, integrating hardware, controls, and packaging across the engine, transmission, generator, and aftertreatment systems.
• Coordinate subsystems and lead technical trade-off discussions across different engineering domains to achieve an optimized system-level solution.
• Drive project milestones and workstream coordination using the Global Technical Development System (GTDS) to ensure timely delivery of project goals.
• Develop and maintain core systems engineering and quality documentation, including Boundary Diagrams, P-Diagrams, and Design Failure Mode and Effects Analysis (DFMEA).
• Define attribute targets and cascade system/subsystem requirements, functions, and use cases to ensure compliance throughout the vehicle's full useful life.

Gasoline Emissions Systems Engineer

Project Manager

• Global Process & Tool Architecture: Serve as a global Subject Matter Expert (SME) for part procurement, return and analysis.
• Workflow Optimization Strategy: Support development of global initiatives and standardized protocols aimed at reducing lead times and removing friction from the end-to-end return workflow.
• Standardization & Playbook Development: Coordinate and maintain the "Global Playbook" of comprehensive process documentation, ensuring a consistent and scalable approach to part analysis worldwide.
• Technical Protocol Alignment: Support the global effort to align all the part return practices (e.g., Escalation of Parts with no Results in WPA).
• Out-of-Warranty Strategy: Support definition of the global framework and legal/logistical pathways for retrieving critical out-of-warranty parts for engineering investigations.
• Tool Management: Support design of the data structures and tool requirements that ensure integrity and efficiency across all global regions.
• Global Quality Awards Coordination: Coordinate the strategic planning and logistical execution of the annual Global Quality Awards, overseeing the nomination process and event coordination.

Global Part Procurement Coordinator

DevOps Engineer

• Team Leadership: Managing and mentoring DevOps engineers, overseeing project workflows, and setting team goals.
• Infrastructure Management: Building, testing, and maintaining cloud platforms (e.g., AWS, Azure, GCP) and infrastructure as code.
• Pipeline Automation: Building and optimizing CI/CD pipelines to ensure efficient software delivery.
• System Reliability & Monitoring: Monitoring software performance, troubleshooting system errors, and implementing preventative measures to ensure high uptime.
• Collaboration & Process Improvement: Bridging development and operations teams, improving collaboration, and optimizing development workflows.
• Security & Compliance: Ensuring security best practices are implemented throughout the software development lifecycle.

Engineering Manager – DevOps, SRE

Data Engineer

• Design and implement end-to-end data pipelines (ETL/ELT) that ingest, process, and curate large-scale enterprise data, including telemetry/vehicle data and other structured/unstructured sources.
• Build and maintain Gen AI pipelines — including embedding generation, vector store indexing, retrieval-augmented generation (RAG), and LLM orchestration — to enable intelligent search, summarization, and conversational analytics over enterprise data.
• Migrate and modernize data assets to a centralized data platform (e.g., BigQuery) using principled data lake/warehouse architectures (Bronze/Silver/Gold or Medallion architecture) to power analytics, reporting, and AI/ML workloads.
• Architect scalable data models and data warehouses, optimizing for query performance, maintainability, cost efficiency, and downstream AI consumption.
• Develop and operate robust orchestration pipelines using Airflow/Astronomer or Schedule Query, with secure, reproducible CI/CD workflows (Terraform + Git) for both data and AI artifacts.
• Integrate LLM APIs and AI services (e.g., Vertex AI, OpenAI, LangChain) into data workflows to automate data enrichment, classification, anomaly narratives, and natural-language interfaces.
• Build and maintain reliable data and model quality checks, lineage, and monitoring with observability tools (e.g., Splunk, Looker/Grafana/Tableau/Power BI dashboards) to rapidly detect and resolve data and AI pipeline issues.
• Implement data governance, security, and compliance controls (data lineage, access controls, PII/PHI protection, prompt injection safeguards, responsible AI guardrails) in collaboration with security and privacy teams.
• Lead the design and delivery of analytics-ready and AI-ready data assets for cross-functional teams, including dashboards, alerts, self-service analytics, and AI-powered insight tools.
• Evaluate, prototype, and productionize emerging Gen AI capabilities (agents, function calling, fine-tuning, multimodal models) to solve business problems and improve platform intelligence.
• Mentor and coach junior engineers on data engineering, AI/ML integration patterns, prompt engineering best practices, and documentation standards.
• Collaborate with data scientists, ML engineers, product managers, and business stakeholders to translate requirements into scalable data and AI solutions and timely insights.
• Monitor cost and capacity planning for cloud and AI resources; optimize storage, compute, and token usage across GCP services (BigQuery, Dataflow, Dataproc, GCS, Vertex AI).
• Participate in on-call rotations and incident response to maintain high availability of data and AI services.

Data Engineer – Full Stack

• Develop and maintain US M&S Financial Albatross
• Support consolidation of profit reporting inputs for Ford Blue management schedules (issue-to-issue, year-over-year, quarter-to-quarter), including input to IMPRS database
• Verify accuracy of IMPRS absolutes and variances for U.S. Blue
• Support identification and research of key issues; support advisement of management on findings / outcome
• Support submission to U.S. Blue FP&A including ad hoc analysis
• Support review U.S. M&S Forecast/ Business Plan / Budget with U.S. M&S Management and Ford Blue CEO
• Manage U.S. M&S calendar and communicate key deadlines and reviews
• Develop and communicate U.S. New Vehicle Net Revenue / Net Pricing metrics for Business Plan, Budget, Forecasts and Actuals
• Coordinate communication and develop quarterly North America Net Revenue / Net Pricing backup to support earnings release process
• Support submission of M&S financial input (quarterly or as requested) to assist in Ford Blue objective/target development
• Support submission of M&S financial backup for all Board of Directors meetings
• Support other monthly forecast requests such as Budget Performance and other ad hoc support
• Complete annual file review and comply with other Internal Control requirements
• Support GM organizations with monthly forecast and Business Plan analysis
• Support U.S. Blue forecast accuracy performance analysis and reporting
• Calculate monthly U.S. price protection accrual and journal entry during monthly actuals (all segments)
• Complete quarterly U.S. and Canada price protection reserve analysis
• Complete breakage analysis based on historical claims % every 6 months

Senior Analyst, M&S US Profit Analysis

Technical Product Manager

• Program planning and execution across multiple vehicle programs and digital platforms, balancing resources, risks, and priorities.
• Develop and maintain integrated schedules, dependency maps, and risk mitigation plans across ADAS feature sets.
• Ensure timely delivery of ADAS capabilities aligned with vehicle launch timelines and regulatory requirements.
• Partner with systems engineering and safety teams to ensure robust functional safety (ISO 26262) and cybersecurity compliance and regulatory compliance.
• Build strong relationships with engineering, product, engineering project managers, manufacturing, and supplier teams to ensure seamless integration and delivery.
• Facilitate cross-organizational collaboration to resolve technical and programmatic challenges.
• Communicate program status, scorecards risks, and decisions clearly and effectively to executive leadership and technical teams.
• Identify and implement process improvements to enhance program execution, quality, and velocity.

ADAS Hardware and Software TPM

QA Engineer

• Define and own the execution of research projects tied to production needs to improve quality, decrease cost, and deliver vehicle level attributes.
• Plan testing of battery cells that are new to Ford with a focus on understanding the affected vehicle level performance attributes.
• Relate battery cell electrode level or material level data and characteristics to cell level performance attributes and failure modes.
• Post-process battery cell, pack, and vehicle test data. Use data to define problems and demonstrate performance to objectives / requirements.
• Work with the R&A and Product Development teams on modeling needs, BMS simulations, or hardware solutions as they relate to solving complex problems.
• Define requirements for /review the design of custom retention fixtures for cell and module testing. Continue to interface with lab testing teams to help identify further iterative design changes.
• Define requirements for instrumentation for given test needs. Continue to interface with lab testing teams to ensure data quality.
• Review fleet / connected vehicle data as it relates to root cause characterization of potential warranty issues or setting requirements/ goals for research project goals.
• Transfer developed technologies/solutions to product teams by supporting verification testing at cell, module, pack or vehicle level.