Solera
Principal Software Engineer
Skills
Job description
Principal Software Engineer
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
Build, Ship, and Own
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)
Proficient with Git and modern development workflows
Strong understanding of testing strategies and production-quality code
NICE TO HAVE
Experience with Java or polyglot environments
Background with message queuing and event streaming (Kafka, RabbitMQ, ActiveMQ)
Deep experience with Redis or distributed caching
Frontend framework experience (React, Angular, Vue)
Experience with high-throughput or real-time AI systems
Experience building AI safety, evaluation, or governance frameworks
Strong background in Agile/Scrum environments
EDUCATION
Bachelor’s degree in computer science or equivalent practical experience
WHAT SUCCESS LOOKS LIKE
You are consistently delivering high-impact features, including AI-powered capabilities
AI systems you build are reliable, observable, and trusted in production
Legacy systems are being systematically modernized without disrupting the business
Teams move faster because of the patterns, tools, and examples you set
Engineers seek you out for guidance on complex systems and AI design decisions
Projects you lead are well-scoped, well-communicated, and delivered through effective collaboration with product, engineering, operations, and business stakeholders
Code quality, reliability, and development velocity improve measurably
You are recognized as a technical leader who ships and elevates everyone around them