Sr. Systems Engineer - Design and R&D

설명

The Role

The Global Design and R&D IT team supports the design and research and development of GM production and concept vehicles, from early innovation through production design. We are seeking a highly motivated Sr. Systems Engineer to define, analyze, integrate, and evolve AI-enabled systems that support Global Design and Product Development engineering teams.

This is a blended systems engineering and systems analysis role. You will translate complex business and engineering needs into practical system solutions, evaluate opportunities to apply AI, and guide capabilities from discovery through production. You will work across requirements, architecture, data, APIs, applications, and operational processes with a strong focus on business value, security, quality, performance, and reliability.

This role is primarily focused on systems thinking, solution definition, integration, and technical leadership rather than day-to-day application development. You will partner with engineering, data, AI, architecture, and business teams to identify high-value AI opportunities, define system requirements and solution approaches, assess risks and dependencies, and guide delivery teams toward successful outcomes.

What You'll Do

• Lead discovery, systems analysis, solution definition, and continuous improvement for AI-enabled systems supporting Global Design and Product Development engineering teams.
• Facilitate discussions with business and technical stakeholders to understand needs, define problems, identify opportunities, and translate them into clear objectives and delivery plans.
• Identify and assess potential AI/ML and large-language-model (LLM) use cases, including business value, data readiness, feasibility, risk, security, privacy, and responsible-use considerations.
• Analyze current-state processes, applications, data flows, interfaces, and dependencies to identify gaps, risks, inefficiencies, and opportunities for modernization.
• Define future-state capabilities, system boundaries, integration patterns, solution options, and functional and non-functional requirements aligned with enterprise standards.
• Partner with data science, AI, software, and data engineering teams to guide AI capabilities from concept through production, including retrieval and inference integrations, evaluation, monitoring, guardrails, and continuous improvement.
• Define data requirements, data-quality expectations, lineage needs, validation rules, and data-access patterns for AI-enabled and data-intensive solutions.
• Define and evaluate API, integration, and interface requirements that connect data, business processes, AI services, and engineering workflows.
• Assess and recommend technology and architecture approaches across cloud platforms, databases, Databricks, APIs, containers, and AI services.
• Use working knowledge of SQL, Databricks, Java, and Python to evaluate solution designs, validate assumptions, analyze data needs, and collaborate effectively with implementation teams.
• Create system models, process flows, data flows, architecture diagrams, decision records, interface definitions, and other technical documentation that communicate solutions clearly to technical and non-technical audiences.
• Define acceptance criteria, test scenarios, traceability, validation approaches, and operational-readiness criteria in collaboration with product owners, developers, testers, data engineers, architects, and business stakeholders.
• Validate that delivered solutions meet functional requirements, data-quality expectations, security requirements, performance objectives, responsible-AI expectations, and intended business outcomes.
• Lead dependency, risk, issue, and change-impact analysis across systems, data, AI capabilities, and delivery teams.
• Ensure solution designs address appropriate security, privacy, observability, reliability, supportability, and governance requirements.
• Support production readiness and operational improvement through monitoring requirements, service-level objectives, incident analysis, release readiness, and continuous improvement.
• Lead or contribute to Agile/Scrum activities including discovery, backlog refinement, sprint planning, solution estimation, dependency management, and incremental delivery.
• Navigate enterprise processes, dependencies, and governance requirements to remove roadblocks and keep delivery on track.
• Provide technical guidance and mentoring to software engineers, systems analysts, data professionals, and other team members.
• Document system, data, AI, and integration solutions so that knowledge can be reused across business functions as applicable.

Your Skills & Abilities (Required Qualifications)

• Bachelor's degree in Systems Engineering, Computer Science, Software Engineering, Information Systems, Data Science, Engineering, or a related field, or equivalent experience.
• 6+ years of experience in systems engineering, systems analysis , solution architecture, product or platform engineering, data/AI delivery, or a related discipline.
• Demonstrated experience leading discovery and translating complex business and engineering needs into functional requirements, non-functional requirements, solution concepts, technical specifications, and actionable delivery plans.
• Experience analyzing and documenting business processes , current- and future-state capabilities, system interactions, data flows, interfaces, dependencies, and change impacts.
• Experience evaluating, integrating, or operationalizing AI/ML services, LLM APIs , or model-driven capabilities in enterprise or production environments, including evaluation, monitoring, security, and responsible-use considerations.
• Experience working with complex SQL queries , relational data, data transformations, data-quality requirements, and data-access considerations.
• Experience analyzing or supporting data pipelines, ETL/ELT processes, or data-intensive applications using Databricks , Spark , or comparable distributed data platforms.
• Experience defining or evaluating APIs, system integrations, cloud services, and enterprise integration patterns.
• Working knowledge of Java and/or Python sufficient to understand solution designs, assess technical tradeoffs, and collaborate effectively with software and data engineers.
• Understanding of cloud, containerized environments, security practices, observability, testing, release management, and operational-readiness concepts.
• Experience defining acceptance criteria, test scenarios, validation approaches, requirements traceability, and operational-readiness criteria for complex systems.
• Experience working in Agile/Scrum development methodologies, including discovery, backlog refinement, sprint planning, and incremental delivery.
• Strong analytical and problem-solving skills, with the ability to break down complex technical, data, AI, and business challenges into clear, actionable steps.
• Excellent written and verbal communication skills, with the ability to facilitate discussions and communicate effectively with technical and non-technical stakeholders.
• Demonstrated ownership, accountability for quality, and focus on delivering measurable value to internal customers.

What Will Give You a Competitive Edge (Preferred Qualifications)

• Master's degree in Systems Engineering, Data Science, Computer Science, Software Engineering, Engineering, Information Systems, or a related field.
• Experience defining AI product or platform capabilities , including use-case discovery, prompt or model integration, retrieval-augmented generation (RAG), agentic workflows, evaluation frameworks, guardrails, human-in-the-loop controls, or MLOps practices.
• Hands-on experience with Databricks , including Delta tables, notebooks, jobs, workflows, and AI/ML workloads.
• Hands-on experience using SQL, Python, or Java to prototype, validate, analyze, or support AI and data solutions.
• Experience with modern Java frameworks such as Quarkus and with enterprise application or integration platforms.
• Experience migrating applications, data workloads, or AI capabilities to Azure or other cloud platforms, including managed data, messaging, API, and AI services.
• Knowledge of relational and dimensional data modeling, data governance, metadata management, data lineage, and enterprise data-quality practices.
• Experience with systems modeling, architecture frameworks, requirements traceability, interface control documents, or comparable systems-engineering practices.
• Experience with observability and reliability practices, including logging, metrics, tracing, dashboards, alerting, and SRE concepts.
• Experience working with product lifecycle management ( PLM ), digital engineering, visualization, CAD/CAM, simulation, or design technology platforms.
• Experience supporting enterprise modernization, platform integration, or large-scale technology transformation initiatives.
• Experience with Docker, Kubernetes, CI/CD , or other modern software delivery practices.
• Demonstrated ability to influence technical direction, establish reusable patterns and standards, and mentor less experienced engineers and analysts.
• Ability to manage multiple initiatives, priorities, and stakeholder relationships in a fast-paced environment while maintaining high engineering standards.

GM does not provide immigration-related sponsorship for this role. Do not apply for this role if you will need GM immigration sponsorship now or in the future. This includes direct company sponsorship, entry of GM as the immigration employer of record on a government form, and any work authorization requiring a written submission or other immigration support from the company (e.g., H1-B, OPT, STEM OPT, CPT, TN, J-1, etc.)

이 직무는 하이브리드 직무로 분류됩니다. 즉, 선발된 지원자는 특정 근무지로 주 3일 이상(또는 관리자가 지정한 다른 빈도로) 특정 근무지로 출근해야 합니다.

Relocation 지원 혜택은 회사 정책에 따라 자격이 되는 지원자에게 제공됩니다.

다양성 정보

General Motors는 법적으로 금지된 차별을 배제하는 것은 물론 포용성과 소속감을 진정으로 장려하는 직장이 되기 위해 노력하고 있습니다. 당사는 다양성이 보장되는 환경에서 직원들이 역량을 발휘하고 우리 고객을 위한 더 좋은 제품을 개발할 수 있다고 믿습니다. 따라서 입사에 관심 있는 사람이 있다면 포지션별 주요 업무와 자격을 확인하고 본인이 보유한 기술과 능력에 부합하는 모든 포지션에 적극적으로 지원하기를 장려합니다. 지원자는 채용 과정에서 역할 관련 평가(해당하는 경우) 및/또는 채용 전 스크리닝을 통과해야 합니다.  자세한 정보는 GM 채용 과정 안내를 참고하십시오.

공평한 취업 기회 선언 (미국)

General Motors는 공평한 기회를 제공하는 고용주임을 자부합니다.  자격을 만족하는 지원자는 인종과 피부색, 성별, 성적 지향, 성별 정체성, 국적, 장애, 재향 군인 보호법 적용 여부와 상관없이 채용 후보로서 심사를 받습니다. 

숙소 (미국 및 캐나다)

General Motors는 장애인을 포함한 모든 구직자들에게 취업 기회를 제공합니다. 구직이나 취업 지원에 도움이 되는 합리적인 숙소가 필요한 경우 [email protected]으로 이메일을 보내시거나 800-865-7580으로 전화주십시오. 이메일에, 귀하가 요청하는 특정한 숙소에 대한 설명과 귀하가 지원하는 직무와 채용 요청서 번호를 포함해주세요.