Sr. AI Software Engineer (Remote)

Inspira Financial•Oak Brook, IL

6d•Remote

About The Position

The Sr. AI Software Engineer embeds with business teams across Health & Benefits, Retirement & Wealth, operations, contact center, finance, HR, marketing, sales, and engineering to identify opportunities for AI and automation. The role translates business needs into requirements, validates feasibility with prototypes, and builds and deploys governed, measurable AI agents and automations on approved enterprise platforms. It also measures business outcomes, applies governance and compliance controls, creates reusable delivery patterns, and raises AI fluency among supported teams. The position reports business needs, recurring patterns, governance friction points, and tooling gaps to the AI Center of Excellence. It reports to the Sr. Director, AI Center of Excellence, in the Technology Department and has no direct reports.

Requirements

Bachelor of Science degree in Engineering or Computer Science.
3–6 years of software engineering experience shipping and supporting production systems.
At least 2 years of hands-on experience building AI solutions across assistants, agents, workflow automation, retrieval, and document processing.
Demonstrated end-to-end ownership of taking a business idea through requirements, prototyping, and production use.
Ability to define and measure business value, construct a baseline, defend a measurement method, and communicate 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 ability to translate it into implemented controls.
Experience instrumenting telemetry as part of the build process.
Ability to work effectively in unfamiliar business functions, build credibility quickly, influence stakeholders, and build relationships.
Ability to learn and adapt to a changing AI platform and tooling landscape.
Ability to occasionally work outside normal business hours to meet project deadlines.
Prolonged periods of sitting at a desk and working on a computer.

Nice To Haves

AI continuous learning certifications.
Experience in financial services, healthcare, benefits administration, or another regulated industry, particularly with PII, PHI, or fiduciary data.
Process improvement experience, such as Lean, Six Sigma, or process mining.
Fluency in low-code automation platforms alongside code-first development.
Experience with contact center, claims, or back-office operations technology.
Experience developing internal enablement materials, documentation, or practitioner communities.

Responsibilities

Embed with business teams to identify repetitive, automatable, or bottlenecked work.
Translate business needs into written solution statements, success criteria, data requirements, and recommendations on whether AI is appropriate.
Build prototypes to validate feasibility and scope opportunities as agents, workflows, multi-tier agent systems, or approved vendor capabilities.
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.
Design multi-tier agent systems with orchestration, specialized agents, scoped tools, defined boundaries, and human handoffs.
Integrate with business systems using approved connectors and MCP servers, and support approvals for new connectors when needed.
Hand off completed builds with documentation, a runbook, a named owner, and a business user able to operate the solution independently.
Baseline process performance before builds and continuously measure deployed solutions, including cycle time, volume, error and rework rates, handle time, and cost per unit as applicable.
Report outcomes honestly, including unsuccessful builds and lessons learned.
Apply an ISO/IEC 42001 governance mindset, including purpose definition, risk classification, data handling, human oversight, and evidence of control operation.
Define and implement governance, security, and compliance telemetry; build monitoring and alerting for drift, boundary violations, and unexpected spend.
Operate within the AI Governance Committee process and AI Acceptable Use Policy.
Report business needs, governance friction points, recurring patterns, and tooling gaps to the AI Center of Excellence.
Convert repeat builds into reusable patterns, templates, and starter kits.
Run enablement sessions and working labs to raise AI fluency in supported business teams.
Perform other duties as assigned.