Lead Software Engineer

About the job

Lead Software Engineer – AI-Driven Development & Agentic Workflows 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 Lead Software Engineer who can help design, build, and deliver production-grade software with a strong focus on AI-driven development, agentic AI systems, and workflow automation. You will work as a senior technical contributor and workstream lead, writing production code regularly while guiding engineers through complex implementation decisions.

- This role is ideal for an experienced engineer who:

- Builds production software using modern engineering practices and AI-assisted development tools

- Designs and implements agentic AI workflows that connect LLMs, tools, APIs, data sources, and business processes

- Leads delivery for features, services, and workflow automation capabilities within a team or product area

- Applies pragmatic architecture patterns that improve reliability, scalability, maintainability, and developer velocity

- Mentors engineers through hands-on pairing, code review, technical design, and adoption of AI-driven development practices

- You will operate with meaningful autonomy within your team, influence implementation patterns across related services, and be known as someone who ships high-quality software, unblocks delivery, and helps the team adopt practical AI-enabled engineering workflows.

WHAT YOU’LL DO Build, Ship, and Own

- Write production-quality code regularly across services, APIs, workflow engines, and AI-enabled capabilities

- Lead delivery of high-impact features from design through deployment and production support

- Modernize legacy components incrementally using pragmatic, low-risk migration patterns

- Design, build, and evolve scalable microservices, APIs, integrations, and event-driven workflows

- Translate business and product requirements into reliable software designs, implementation plans, and working solutions

- Identify implementation risks early and drive practical solutions that keep delivery moving without sacrificing quality

AI-Driven Development, Agentic AI & Workflow Automation

- Design and implement AI-enabled workflows using large language models, retrieval patterns, structured outputs, and tool/function calling

- Build agentic systems that can execute multi-step workflows, invoke tools, call APIs, maintain state, and support human-in-the-loop reviews where appropriate

- Implement MCP-style or equivalent orchestration patterns for context management, tool access, memory, permissions, and workflow execution

- Integrate AI workflows with enterprise data sources, business applications, APIs, queues, and operational systems

- Apply grounding, validation, guardrails, prompt/version management, and evaluation techniques to reduce hallucinations and improve reliability

- Build monitoring, observability, feedback loops, and quality checks for production AI behavior

- Partner with product, security, architecture, and operations teams to ensure AI solutions meet business, privacy, compliance, and supportability requirements

Technical Leadership & Delivery

- Lead technical execution for a team, feature area, or workstream while remaining hands-on in the codebase

- Contribute to architecture decisions for service boundaries, integration patterns, data ownership, and AI workflow design

- Make sound engineering tradeoffs across delivery speed, reliability, scalability, security, cost, and maintainability

- Serve as a technical escalation point for implementation challenges involving distributed systems, AI workflows, data integrations, and production issues

- Create reusable patterns, examples, and guidance that help engineers deliver consistent, high-quality solutions

AI‑Assisted Engineering & Developer Productivity

- Use AI-powered development tools such as GitHub Copilot, ChatGPT, Claude, or equivalent tools to accelerate coding, refactoring, testing, debugging, and documentation

- Establish practical team practices for safe, reviewable, and high-quality AI-assisted development

- Create prompts, reusable workflows, coding patterns, and automation scripts that improve developer productivity

- Help engineers adopt AI-driven development without weakening code review discipline, testing standards, security practices, or production ownership

Mentorship & Team Elevation

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

- Help engineers build stronger judgment around AI-enabled development, workflow automation, testing, and production readiness

- Coach less-experienced developers on modern engineering practices, secure AI usage, and maintainable system design

- Promote a culture of ownership, learning, collaboration, and technical accountability

- Lead by example with clear communication, humility, urgency, and high engineering standards

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

- 7+ years of professional software development experience

- Proven experience leading delivery of complex features, services, or technical workstreams

- Hands-on experience designing, building, and operating production software systems

- Experience applying AI-assisted development tools in real engineering workflows

- Hands-on exposure to LLM-enabled applications, agentic workflows, automation systems, or AI-integrated product capabilities

- Demonstrated ability to mentor engineers and improve team execution through practical technical leadership

Technical Skills

- Strong proficiency in C# and .NET, including ASP.NET Core and modern .NET development

- Frontend framework experience such as React, Angular

- Strong understanding of RESTful API design, distributed systems, and production service development

- Experience building microservices, integration services, and event-driven workflows

- Hands-on experience with LLMs, AI workflow orchestration, or agentic AI patterns, including tool/function calling, context management, structured outputs, and workflow state

- Experience integrating AI-enabled systems with databases, APIs, queues, and enterprise applications

- Hands-on experience with relational databases such as SQL Server or PostgreSQL

- Working knowledge of NoSQL data stores, caching strategies, and performance optimization

- Experience with Docker, containerized application development, and cloud deployment practices

- Practical experience with Kubernetes or container orchestration platforms

- Comfort working in cloud environments such as Azure or AWS

- Proficient with Git, pull requests, code reviews, branching strategies, and modern CI/CD workflows

- Strong understanding of automated testing, observability, secure coding, and production support practices

Must Have Skills:

- Strong proficiency in C# and .NET, including ASP.NET Core and modern .NET development

- Frontend framework experience such as React(Preferable) , Angular

- Hands-on experience with relational databases such as SQL Server

- Hands-on experience with LLMs , AI workflow orchestration, or agentic AI patterns, including tool/function calling, context management, structured outputs, and workflow state

- Develop production-quality code across distributed services and architecture , leveraging expertise in APIs, workflow orchestration, and AI-enabled solutions.

NICE TO HAVE

- Experience with Python, Java, TypeScript, or polyglot engineering environments

- Experience with message queues, event streaming, or workflow orchestration platforms

- Experience with vector databases, retrieval-augmented generation, knowledge graphs, or semantic search

- Experience building AI evaluation harnesses, prompt/version management, safety checks, or governance workflows