Lead Software Engineer - AI & Machine Learning
Salary not listed • OH, United States • Full-time
Posted 24d ago
No salary is listed. Many US states require employers to post a pay range, so ask about pay early.
Remote Work Policy
On-site
Employment Type
Full-time
Categories
LLM Engineer
About the job
As a Lead Software Engineer within Corporate Technology and the AI/Machine Learning & Automation Center of Excellence, you will drive the scalable adoption of responsible AI and intelligent automation. This involves defining standards, reference architectures, and governance frameworks that various teams can consistently implement. You will influence outcomes across a federated delivery model by enabling reuse, aligning stakeholders, and embedding practical frameworks to improve delivery speed, resiliency, and control adherence.
Responsibilities
- Drive enterprise alignment and adoption of AI/machine learning and intelligent automation by partnering with engineering, product, and business teams.
- Influence cross-functional stakeholders to align priorities across federated teams and reduce fragmentation.
- Define, maintain, and evolve scalable reference architectures, implementation patterns, and standards.
- Enable reuse at scale by promoting shared tooling, accelerators, and reusable capabilities.
- Provide advisory support and constructive challenge to delivery teams on AI-enabled solutions.
- Establish and reinforce Responsible AI governance across distributed teams, including ethical AI use, bias mitigation, and data quality.
- Promote secure, resilient, and scalable engineering practices aligned to enterprise architecture expectations.
- Lead and contribute to a community of practice to uplift capability and share patterns.
- Drive team adoption of enterprise-authorized AI-assisted engineering practices to improve code quality and delivery speed.
- Apply knowledge of AI-assisted development and automation capabilities within the Software Development Life Cycle toolchain.
Requirements
- Formal training or certification on software engineering concepts and 5+ years of applied experience.
- Demonstrated ability to influence and align senior stakeholders across multiple teams in a large, complex organization without direct authority.
- Experience operating within an enterprise enablement function or center of excellence model focused on standards, governance, and scaled adoption.
- Strong understanding of AI/machine learning, generative AI (LLMs and SLMs), NLP, and intelligent automation concepts, with emphasis on enablement.
- Solid grounding in modern engineering practices, including SDLC, scalable system design, and operational resilience.
- Experience designing or governing cloud-based architectures leveraging APIs, microservices, and integration patterns at enterprise scale.
- Proven ability to define and embed Responsible AI governance across distributed teams.
- Demonstrated experience leading effective use of approved AI-assisted software development tools and setting team expectations for validating AI outputs.
- Strong understanding of responsible AI use in engineering workflows, including data sensitivity, secure handling of inputs/outputs, and adherence to resiliency and security expectations.