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Solera Holdings

Data platform for insurance and automotive

Principal Software Engineer

AI Application Engineering +1Confirmed live in the last 24 hours
Full-timeBengaluru, Karnataka, IndiaNo salary listedIn-person

About the Job

Requirements

  • At least 10 years of professional software development experience.
  • Proven experience owning and delivering large, complex systems.
  • Demonstrated success modernizing legacy systems and technology 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.
  • Ability to lead a complete project independently, coordinate with cross-functional stakeholders, manage technical risks, and drive execution through delivery.
  • Expert-level proficiency in C# and .NET, including ASP.NET Core and 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, and AI workflow orchestration such as MCP-style patterns.
  • Experience integrating AI systems with datastores, APIs, and event-driven workflows.
  • Hands-on experience with relational databases such as SQL Server and PostgreSQL.
  • Working knowledge of NoSQL data stores and caching strategies such as Redis.
  • Strong experience with Docker and production containerization.
  • Practical experience with Kubernetes and container orchestration.
  • Comfort working in AWS and/or Azure cloud environments.
  • Proficiency with Git and modern development workflows.
  • Strong understanding of testing strategies and production-quality code.
  • Experience with a frontend framework such as React or Angular.
  • Bachelor’s degree in computer science or equivalent practical experience.

Responsibilities

  • 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.
  • 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 or equivalent to manage context propagation, tool invocation, state and memory, and 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.
  • 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 challenging distributed systems, data, and AI workflow problems.
  • Influence technical direction across multiple teams without becoming a bottleneck.
  • Provide technical leadership for projects by coordinating architecture, engineering execution, dependency management, risk mitigation, and cross-team alignment.
  • Communicate with product owners, engineering leaders, security, DevOps/SRE, QA, and business stakeholders to keep delivery aligned with business outcomes.
  • Leverage AI-powered development tools such as GitHub Copilot, ChatGPT, and Claude 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.
  • 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.
  • 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, including design, coding, testing, deployment, and production support.

Desired Qualifications

  • 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.
  • Background with high-throughput, real-time, or operationally critical SaaS systems.
  • Experience in Agile/Scrum environments and cross-functional delivery.

About the Company

Solera Holdings

Data platform for insurance and automotive

Solera is a global provider of data, applications, and services for the insurance and automotive industries. It offers a unified platform that combines data, insights, and algorithms to help insurers and automotive professionals connect, streamline operations, and improve decision-making, with a revenue model based on subscriptions, transaction fees, and value-added services. The company serves over 250,000 customers in 90 countries and processes more than 300 million transactions each year. Solera differentiates itself by offering an end-to-end, industry-specific platform and professional workflows at scale, rather than a single tool. Its goal is to help clients achieve better customer outcomes and stay aligned with industry trends through reliable technology, integrity, and customer success.

Company size
1,001-5,000
Company stage
IPO
Headquarters
Westlake, TX
Founded
2005

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