below marketmost similar roles pay hereabove market
This role pays less than
76%
of similar roles. Most pay
$167,500–$236,128
— the blue band above.
At the midpoint, this role pays about
$166k
versus about
$202k
for comparable roles.
Based on 240 similar postings.
Employer
About Lyft
Lyft is a transportation network company offering ride-hailing services across the US and Canada.
Lyft currently has
35 open roles
on FindRole.
Listed pay typically runs
$148,000–$185,000
across 30 roles with salary data.
The Senior AI Software Engineer, Risk - Insurance Claims Management joins the Risk Tech engineering organization to develop a Unified Risk Platform for insurance claims management. This role involves defining the long-term technical roadmap, providing architectural leadership, and driving the development of a scalable, intelligent Risk Management Information System. You will build end-to-end solutions to automate claim handling workflows, resolve operational bottlenecks, and manage complex financial liabilities and regulatory processes. Key responsibilities include leading code reviews, managing production on-call support, and collaborating with Data Science and Product teams. Required skills include proficiency in Python, experience with Spark, Kafka, and Airflow, and expertise in building AI features using multimodal LLMs, RAG pipelines, and agentic workflows. You must demonstrate ability in system design, domain modeling, and optimizing performance through robust evals.
Define and drive the long-term technical roadmap for claims management systems.
Provide architectural leadership and make informed design tradeoffs across multiple engineering teams.
Identify workflow bottlenecks and resolve pain points using AI automation solutions.
Deliver scalable, reliable, and well-tested code for the Risk Management Information System.
Coordinate technical alignment and scalable integrations with internal teams and external insurance partners.
Lead code reviews, design reviews, production on-call support, and incident triaging.
Share knowledge through tech talks and suggest improvements to engineering practices.
What we're looking for
B.S. or M.S. in Computer Science or a 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 while collaborating with Backend, Frontend, Data Engineering, Data Science, 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 with data processing frameworks and tools like Spark, Kafka, Airflow, and cloud provisioning environments.
Proficiency in Python.
Prior experience in insurance, claims management, workflow orchestration, or external vendors (preferred).
Knowledge of AI safety and alignment considerations (preferred).
Background in machine learning, NLP, or related fields (preferred).
Experience with A/B testing and experimentation frameworks (preferred).