Senior AI Software Engineer, Risk - Insurance Claims Management

At Lyft, our mission is to improve people's lives with the world's best transportation. To accomplish this, we start with our community by creating an open, inclusive, and diverse organization.

The Risk Tech engineering organization is committed to tangibly reducing accident frequency, saving lives, and managing costs to enhance the safety and affordability of rides.

Claim Management is a core financial function for Lyft. Each claim touches complex workflows, multiple stakeholders, sensitive data, financial reserves, regulatory processes, and significant financial liabilities.

This role offers the opportunity to define a leading claims management system for the industry. Our vision is to establish a single, Unified Risk Platform where comprehensive claims workflows across all business lines are efficiently administered, communications are consolidated, and data is structured to facilitate data-driven insights and decisions.This enables cost-efficient claims operations, mitigates risks and expenses as Lyft scales, and ensures people receive assistance proactively and accurately.

We are seeking a Senior Software Engineer to contribute to the technical direction, drive architectural decisions, and lead the development of a highly reliable, scalable, and intelligent Risk Management Information System that powers our insurance platform. You will collaborate with passionate colleagues from Engineering, Data Science, Product and Claim Operations to deliver end-to-end solutions.

• Define and drive the long-term technical roadmap for claims management systems, aligning priorities with Product, Claim Operations, Data Science, and other stakeholders.

• Provide architectural leadership, make informed design tradeoffs, and guide strategic decisions across multiple engineering teams.

• Understand claim handling workflows, identify bottlenecks and multiply their productivity by driving platform innovations and resolving pain points with AI automation solutions

• Deliver scalable, reliable, high quality and well-tested solutions and code.

• Collaborate closely with Lyft internal teams and external insurance partners to ensure technical alignment and scalable integrations.

• Lead code reviews, design reviews, production on-call support and incident triaging process.

• Invest in the engineering community through knowledge sharing via brown bags, tech talks, and suggesting improvements to team processes and engineering practices.

• B.S., M.S. in Computer Science or related technical field or relevant work experience.

• 6+ years of professional experience building scalable distributed systems with high availability, observability and reliability requirements.

• Proven ability to build end-to-end products and platforms, collaborating effectively with various stakeholders e.g. Backend, Frontend, Data Engineering, Data Science, Claim Operations, and Product teams.

• Strong ability to reason about tradeoffs in system design, architecture, domain modeling, and operational cost.

• Experience developing AI features using multimodal LLMs, RAG pipelines, agentic workflows, and other relevant AI frameworks.

• Experience driving AI adoption or AI automation tools to enhance development efficiency

• Experience improving performance with robust evals,agent tracing tools, fine-tuning LLMs, optimizing RAG pipelines and implementing feedback loops.

• Proficiency in Python. Knowledge of React/Next.js and data analysis is a plus.

• Experience with data processing frameworks and tools like Spark, Kafka, Airflow and cloud provisioning environments etc.

• Prior experience in insurance, claims management, workflow orchestration or external vendors is a strong plus.

• Has knowledge about AI safety and alignment considerations.

• Experience with A/B testing and experimentation frameworks

The expected base pay range for this position in the San Francisco area is $148,000 - $185,000 , not inclusive of potential equity offering, bonus or benefits. Salary ranges are dependent on a variety of factors, including qualifications, experience and geographic location. Your recruiter can share more information about the salary range specific to your working location and other factors during the hiring process.