Principal Software Engineer

About the job

Who We Are Solera is a global leader in data and software services, transforming every touchpoint of the vehicle lifecycle into a connected digital experience. Solera processes over 300 million digital transactions annually for approximately 235,000 partners and customers in more than 90 countries. Our teams work on mission‑critical platforms that demand reliability, scalability, and thoughtful evolution of complex systems.

Job Summary We’re looking for a hands-on Principal Software Engineer (P5) who is deeply focused on AI-driven development, agentic AI systems, and practical delivery of production software. This person will not only set the technical direction but also take full ownership of complex initiatives—leading projects from concept through architecture, implementation, launch, and continuous improvement.

This role is ideal for a senior technologist who:

- Leads complete, high-impact projects end-to-end with strong technical ownership, execution discipline, and stakeholder alignment

- Designs and builds AI-driven software solutions using LLMs, agentic architecture, MCP-style orchestration, and AI-enabled automation

- Makes pragmatic architectural decisions that balance speed, reliability, and long-term maintainability

- Leverages AI-assisted development tools to accelerate delivery and elevate team productivity

- Partners effectively with product, architecture, security, operations, and business stakeholders to turn ambiguous goals into delivered outcomes

- Mentors engineers and raises the overall technical standard through example, code review, and system ownership

- You will operate with broad autonomy, lead complete initiatives without requiring constant direction, influence architectural direction across teams, and be known as someone who ships, unblocks others, aligns stakeholders, and makes things happen.

WHAT YOU’LL DO

- Write production-quality code regularly across core services, platforms, and AI workflows

- Own and deliver high-impact features and system improvements end-to-end

- Lead the modernization of legacy systems, incrementally migrating to modern, cloud-native architectures

- Design, build, and evolve scalable microservices and APIs

- Translate ambiguous business requirements into reliable, working software quickly

- Identify technical risks early and drive pragmatic, production-ready solutions

- Run complete project workstreams independently, including technical discovery, solution design, delivery planning, execution tracking, launch readiness, and post-launch follow-through

AI-Driven Development, Agents & LLM Systems

- Lead the design and implementation of AI-driven development patterns, AI processing pipelines, and production-grade LLM capabilities

- Build and orchestrate agentic AI systems capable of tool use, multi-step reasoning, workflow automation, task planning, and autonomous execution with appropriate human oversight

- Implement MCP-style patterns (model–context–protocol or equivalent) to manage:

- Context propagation

- Tool invocation

- State and memory

- Guardrails and policy enforcement

- Integrate AI systems with real business workflows, APIs, and data sources

- Implement hallucination mitigation strategies, such as grounding, retrieval, validation, and structured outputs

- Design evaluation, monitoring, and feedback loops for AI behavior in production

- Ensure AI systems meet security, privacy, and compliance requirements

- Define engineering practices for AI-assisted development, including prompt patterns, code generation workflows, review standards, evaluation criteria, and safe adoption across teams

Technical Leadership & Architecture

- Set and evolve architectural standards through real-world implementation

- Guide service boundaries, data ownership, and integration patterns across systems

- Make principled tradeoffs between speed, scalability, correctness, and cost

- Act as a technical escalation point for the most challenging problems (distributed systems, data, AI workflows)

- Influence technical direction across multiple teams without becoming a bottleneck

- Provide full technical leadership for projects by coordinating architecture, engineering execution, dependency management, risk mitigation, and cross-team alignment

- Communicate clearly with product owners, engineering leaders, security, DevOps/SRE, QA, and business stakeholders to keep delivery aligned with business outcomes

AI‑Assisted Engineering & Developer Productivity

- Leverage AI-powered development tools (GitHub Copilot, ChatGPT, Claude, etc.) to accelerate development

- Establish best practices and guardrails for safe, high-quality AI-assisted coding

- Use AI tools for solution design, refactoring, test generation, debugging, system comprehension, documentation, and accelerating high-quality delivery

- Help teams adopt modern workflows that improve velocity while maintaining engineering rigor

Mentorship & Team Elevation

- Mentor engineers through pairing, code reviews, and design discussions

- Help senior engineers grow into broader technical leadership roles

- Coach less-experienced developers on modern engineering and AI-aware practices

- Foster a culture of continuous learning, ownership, and technical excellence

- Lead by example with clear communication, humility, and accountability

Technical Execution & Operations

- Build and maintain SaaS applications using modern frameworks and cloud platforms

- Design and implement RESTful APIs and event-driven integrations

- Work with relational and NoSQL databases, optimizing for performance and reliability

- Build containerized applications using Docker and deploy via Kubernetes

- Partner with DevOps/SRE to ensure strong CI/CD pipelines, observability, and safe deployments

- Participate fully in the SDLC: design, coding, testing, deployment, and production support

REQUIRED QUALIFICATIONS Experience

- 10+ years of professional software development experience

- Proven experience owning and delivering large, complex systems

- Demonstrated success modernizing legacy systems and tech stacks

- Hands-on experience designing, building, and shipping AI-driven and agentic AI systems in production or production-like environments

- History of hands-on technical leadership across teams or domains

- Strong track record of mentoring and developing engineers

- Proven ability to lead a complete project independently, coordinate with cross-functional stakeholders, manage technical risks, and drive execution through delivery

Technical Skills

- Expert-level proficiency in C# and .NET (ASP.NET Core, modern .NET)

- Deep understanding of RESTful API design and distributed systems

- Strong experience with microservices architectures

- Hands-on experience with LLMs and AI processing systems, including:

- Agentic AI architectures and autonomous workflow execution

- Tool/function calling

- Context and memory management

- AI workflow orchestration (e.g., MCP-style patterns)

- Experience integrating AI systems with datastores, APIs, and event-driven workflows

- Hands-on experience with relational databases (SQL Server, PostgreSQL)

- Working knowledge of NoSQL data stores and caching strategies (e.g., Redis)

- Strong experience with Docker and production containerization

- Practical experience with Kubernetes and container orchestration

- Comfort working in cloud environments (AWS and/or Azure)