Principal AI Engineer

Principle Software Engineer/Mitikah

Who We Are

Solera is a global leader in data and software services that strives to transform every touchpoint of the vehicle lifecycle into a connected digital experience. In addition, we provide products and services to protect life’s other most important assets: our homes and digital identities. Today, Solera processes over 300 million digital transactions annually for approximately 235,000 partners and customers in more than 90 countries. Our 6,500 team members foster an uncommon, innovative culture and are dedicated to successfully bringing the future to bear today through cognitive answers, insights, algorithms and automation.For more information, please visit solera.com.

The Role

The Principal AI Engineer is a senior technical leader who acts as a force multiplier across engineering teams, owning the design, build, and operation of the AI harnesses and agent delivery swarms that accelerate how we ship software. This is an individual-contributor leadership role: you set technical direction and raise the capability of everyone around you without carrying formal people-management responsibilities, though junior engineers may report to you on a dotted-line basis for mentorship and technical guidance. You are the person who makes AI-accelerated delivery real by turning agentic tooling from experiments into dependable, production-grade capacity.

You will architect and continuously improve the frameworks, guardrails, and orchestration that let teams safely delegate work to AI software development agents at scale. Working across greenfield builds and modernization efforts, you leverage our platform approach, enterprise data lake, and strong AI harnesses to dramatically increase delivery throughput and quality. A qualified candidate is a deeply technical engineer with elite hands-on skills, sharp judgment about where AI creates leverage, and a track record of building tools and patterns that other engineers adopt. This role is critical because it defines and scales the AI-native way we build by multiplying the output of every team while keeping quality, security, and reliability high.

What You’ll Do

* Build, own, and continuously improve the AI harness - the frameworks, prompts, context pipelines, guardrails, and evaluation systems that let teams reliably delegate work to AI software development agents

* Design and operate agent delivery swarms, orchestrating multiple AI agents to execute complex build and modernization tasks in parallel with strong review, safety, and quality controls

* Act as a force multiplier for engineering teams embedding with them to accelerate delivery, unblock hard technical problems, and raise the ceiling of what AI-accelerated teams can produce

* Set technical direction and best practices for AI-native software delivery, and drive adoption of these patterns across multiple teams and products

* Provide technical mentorship and dotted-line leadership to junior engineers growing their skills in AI tooling, agent orchestration, and modern engineering practices

*Own architecture and design for AI-accelerated delivery systems partnering with central architecture teams on cross-cutting changes while retaining decision authority for the AI harness and agent tooling

* Establish evaluation, observability, and quality gates for AI-produced code ensuring agent output meets standards for correctness, security, reliability, and maintainability

* Integrate AI capabilities with CI/CD pipelines so agent-generated work flows through automated build, test, and safe-release processes (canary, blue/green, phased rollout)

* Leverage the enterprise data lake and platform services to ground agents in real context, power AI-driven features, and maximize reuse over rebuilding

* Drive both greenfield and modernization work through AI acceleration, sequencing where agent swarms deliver the most leverage and de-risking legacy change

* Evaluate and adopt emerging AI tools, models, and techniques prototyping rapidly and bringing proven approaches into production practice

What You’ll Bring

* 8+ years of hands-on software engineering experience with a track record of operating at a principal / staff+ technical level as an individual contributor

* Bachelor's or Master's degree in Computer Science, Engineering, or a related field or equivalent practical experience

* Deep, current expertise building with AI development agents and agentic tooling designing AI harnesses, prompt/context pipelines, evaluation frameworks, and multi-agent orchestration ("swarms")

* Elite hands-on engineering skills across the full delivery lifecycle, with the ability to build tools and frameworks that other engineers adopt

* Strong architecture and system design skills able to own architectural decisions and partner effectively with central architecture teams

* Deep expertise in CI/CD and safe delivery practices (automated testing, canary, blue/green, phased rollouts, observability, secure delivery)

* Experience with platform / shared-services approaches and data lake / data platform capabilities, and a strong bias for reuse and leverage

* Proven ability to act as a force multiplier mentoring engineers, influencing without authority, and driving adoption of new practices across teams

* Excellent technical communication and collaboration skills able to align diverse teams on AI-native delivery approaches

* A rapid-experimentation mindset staying current with emerging models/tools and translating them into production-grade practice responsibly

It is impossible to list every requirement for, or responsibility of, any position.  Similarly, we cannot identify all the skills a position may require since job responsibilities and the Company’s needs may change over time.  Therefore, the above job description is not comprehensive or exhaustive.   The Company reserves the right to adjust, add to or eliminate any aspect of the above description.  The Company also retains the right to require all employees to undertake additional or different job responsibilities when necessary to meet business needs.