Senior Software Engineer - Enterprise AI Products

What Is the Opportunity?

As a member of Enterprise AI & Emerging Tech, you'll be joining a strategic and collaborative team that is passionate about transforming our business and technology capabilities and paving the way for best-in-class technology, data and analytics. As a Senior Software Engineer for the Enterprise AI Products Value Stream within the Enterprise AI & Emerging Tech organization, you will serve as an organizational technical leader and a driving force behind the engineering standards, architecture decisions, and delivery outcomes of the team.

Engineers at this level work across the full arc of AI product delivery — from long-horizon strategic initiatives where the path to production is known and the engineering complexity is high, to engagements that demand rapid, high-quality delivery directly alongside Lines of Business.

What Will You Do?

• Design and lead the delivery of production-grade AI-powered solutions across a range of engagement types — from sustained strategic initiatives requiring deep discovery, architecture ownership, and long-horizon planning, to rapid field engagements focused on integrating LOB workflows with enterprise AI platforms and validating feasibility through working prototypes.
• Drive technical decisions across multiple teams, establishing patterns and engineering standards that are adopted beyond the immediate team and serve as a reference for the broader organization.
• Lead stakeholder conversations with Lines of Business — translating complex technical capabilities into terms that communicate clear business value, and surfacing field intelligence that shapes strategic investment decisions and roadmap priorities.
• Apply production-hardened machine learning experience to the design and evaluation of AI systems — including model selection, fine-tuning, evaluation methodology, feature engineering, and the integration of traditional ML fundamentals alongside modern LLM-based approaches.
• Own the technical quality of what the team ships — driving adherence to nonfunctional requirements including modularity, scalability, observability, recoverability, and testability across all delivered capabilities.
• Mentor engineers across the team and beyond, setting the learning example, defining best practices, and building engineering capability at an organizational level.
• Advocate for and advance engineering practices across the value stream — including source code management, CI/CD standards, test automation, and modern engineering principles — with an expectation of alignment across teams, not just your own.
• Identify opportunities where technology can drive business value, think proactively two to three quarters ahead, and contribute to the technical strategy of the AI Products value stream.
• Participate in and lead Engineering Chapter events and cross-organizational technical forums, sharing knowledge in a discoverable and enterprise-accessible way.
• Perform other responsibilities as assigned.

What Will Our Ideal Candidate Have?

• 5+ years of software engineering experience with proficiency in Python; additional languages (JavaScript, TypeScript, Java) a plus.
• Hands-on experience with AWS and/or Azure, containerization and orchestration (Kubernetes), RESTful APIs, microservices architecture, and CI/CD tooling (Jenkins or GitHub Actions).
• Production experience designing and delivering agentic workflows, LLM integrations, or AI-powered automations; applied ML experience including model development, training, fine-tuning, and evaluation.
• Demonstrated ability to lead architecture and solution design across teams; advanced delivery skills including design strategy, automated testing, feedback loops, and production health monitoring.
• Strong problem solver — uses data and proofs of concept to find creative solutions, measures impact, and optimizes; comfortable making decisions with broad implications and significant complexity.
• Strong communicator — able to translate complex technical capabilities into business terms, document initiatives clearly, lead stakeholder conversations, and foster inclusive, collaborative team environments.
• Advanced leadership skills — takes ownership in ambiguous situations, influences priorities, develops business partnerships, mentors others, and shares knowledge across the organization.
• Familiarity with Terraform, MongoDB or comparable NoSQL, Temporal or comparable workflow orchestration, and MCP server configurations and multi-agent frameworks.
• Experience with ML observability, drift detection, model performance monitoring, or distributed tracing in production environments.
• Familiarity with zero-trust security principles or secure-by-design development practices in enterprise AI systems.
• Experience establishing or contributing to engineering standards at an organizational level.

What is a Must Have?

• Bachelor’s degree in computer science, related STEM field, or its equivalent in education and/or work experience.
• 6 additional years of software engineering experience.