Senior AI Software Engineer, Risk - Insurance Claims Management

At Lyft, our purpose is to serve and connect. We aim to achieve this by cultivating a work environment where all team members belong and have the opportunity to thrive.

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.

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.
Strong oral and written interpersonal skills.
Preferred:
Prior experience in insurance, claims management, workflow orchestration or external vendors is a strong plus.
Has knowledge about AI safety and alignment considerations.
Background in machine learning, NLP, or related fields.
Experience with A/B testing and experimentation frameworks