Sr. AI Software Engineer (Remote)

The Sr. AI Software Engineer reports to the Sr. Director, AI Center of Excellence, in the Technology Department, and has no direct reports. Be a part of a growing team that is directly impacting the way our business operates. In this role you embed with business teams across Health & Benefits, Retirement & Wealth, operations, contact center, finance, HR, marketing, sales, and engineering. You are a consultant at the edge of our internal teams, helping to identify AI opportunities, define requirements, build prototypes, and ship governed, measurable AI agents into production. The primary duties include finding and scoping AI-suited business problems; building and shipping production agents and automations on approved enterprise platforms; baselining processes and measuring and reporting ROI before and after deployment; applying AI governance and compliance controls to every build; and converting repeat work into reusable patterns while raising AI fluency across the business teams this role supports. You bring information back to the CoE and deliver value to our business partners. If you love finding new challenges, showing people new was to solve problems, and to build and tinker while delivering critical business value continuously, this role is a perfect fit.

1. →Embed within business teams across Health & Benefits, Retirement & Wealth, operations, contact center, finance, HR, marketing, sales, and engineering to identify work that is repetitive, automatable, or bottlenecked.
2. →Translate and communicate a business need into a written solution statement, success criteria, data requirements, and a documented recommendation on whether AI is the appropriate solution.
3. →Build working prototypes to validate feasibility before committing to a full build.
4. →Scope each opportunity appropriately, determining whether the right solution is a single-purpose agent, an automated workflow, a multi-tier agent system, or an existing approved vendor capability.
5. →Build production agents and automations on approved enterprise platforms, including assistant and agent frameworks, low-code workflow automation, document intelligence, conversational and agent-assist capabilities, and natural language analytics.
6. →Design multi-tier agent systems where an orchestration layer routes to specialized agents with scoped tools, defined boundaries, and a clean handoff to a human.
7. →Integrate with business systems through approved connectors and MCP servers and support the approval process for new connectors when a use case requires one.
8. →Hand off completed builds with documentation, a runbook, a named owner, and a business user able to operate the solution independently.
9. →Baseline process performance prior to each build, capturing cycle time, volume, error and rework rates, handle time, and cost per unit as applicable.
10. →Instrument deployed agents so that value is measured continuously rather than asserted once at launch.
11. →Report outcomes honestly, including builds that did not deliver value and the resulting lessons learned.
12. →Apply an ISO/IEC 42001 governance mindset to every build, including defined purpose, risk classification, data handling, human oversight, and evidence that controls operated as intended.
13. →Define and implement governance, security, and compliance telemetry for each agent, covering tool calls, scope adherence, escalation and override rates, data access, output quality, and cost.
14. →Build monitoring and alerting so drift, boundary violations, and unexpected spend are surfaced to an owner.
15. →Operate within the AI Governance Committee process and the AI Acceptable Use Policy.
16. →Report business team needs, governance friction points, recurring patterns, and tooling gaps back to the AI Center of Excellence.
17. →Convert repeat builds into reusable patterns, templates, and starter kits for use by other consultants and delivery teams.
18. →Run enablement sessions and working labs to raise AI fluency within the business teams this role supports.
19. →Perform other duties as assigned.

Minimum required:

• Bachelor of Science degree in Engineering or Computer Science
• AI Continuous learning certifications are a plus
• 3-6 six years of software engineering experience shipping and supporting production systems.
• 2 +years of hands-on experience building AI solutions across assistants, agents, workflow automation, retrieval, and document processing.

• Demonstrated end-to-end ownership, taking a business idea from initial concept through requirements, prototype, and production use.
• Ability to define and measure business value, including constructing a baseline, defending a measurement method, and communicating cost and benefit independently.
• Working knowledge of at least one AI governance or management framework, such as ISO/IEC 42001 or NIST AI RMF, and the ability to convert it into implemented controls.
• Experience instrumenting telemetry as part of the build process rather than after an incident.
• Ability to work effectively within unfamiliar business functions, build credibility quickly, and influence stakeholders while building relationships.
• Ability to learn and adapt to a changing AI platform and tooling landscape.
• Financial services, healthcare, benefits administration, or other regulated industry experience preferred, particularly environments handling PII, PHI, or fiduciary data.
• Process improvement experience preferred, such as Lean, Six Sigma, or process mining.
• Fluency in low-code automation platforms alongside code-first development preferred.
• Experience with contact center, claims, or back-office operations technology preferred.
• Experience developing internal enablement materials, documentation, or practitioner communities preferred.

• Ability to occasionally work outside normal business hours to meet project deadlines as needed.
• Prolonged periods of sitting at a desk and working on a computer.