Senior AI Software Engineer, Risk

About the role

You will define and drive the long-term technical roadmap for Lyft's claims management systems in collaboration with Product, Claim Operations, Data Science, and other stakeholders. You will provide architectural leadership and make informed design tradeoffs to guide strategic decisions across multiple engineering teams. You will understand claim handling workflows deeply, identify bottlenecks, and multiply productivity by driving platform innovations and resolving pain points with AI automation solutions. You will deliver scalable, reliable, high quality, and well-tested solutions and code that power critical financial operations. You will collaborate closely with Lyft internal teams and external insurance partners to ensure technical alignment and scalable integrations. You will lead code reviews, design reviews, production on-call support, and incident triaging process to maintain system integrity. You will invest in the engineering community through knowledge sharing via brown bags, tech talks, and suggesting improvements to team processes and engineering practices.

Key facts

What you'll do

Define and own the end-to-end architecture for the Unified Risk Platform that consolidates claims workflows, communications, and structured data.

Drive technical priorities and roadmap decisions for claims management systems in close partnership with Product, Claim Operations, Data Science, and other stakeholders.

Analyze and understand complex claim handling workflows, identify systemic bottlenecks, and design platform innovations to multiply team productivity.

Develop and deliver scalable, reliable, high quality, and well-tested software solutions that meet stringent availability and performance requirements.

Collaborate with Lyft internal teams and external insurance partners to design integrations that ensure consistency, compliance, and scalability.

Lead code reviews, design reviews, and ensure engineering standards are met across implementations.

Provide production on-call support and actively participate in incident triaging, root cause analysis, and remediation planning.

Invest in continuous improvement by sharing knowledge through brown bags, tech talks, and evolving team processes and engineering best practices.

Leverage AI technologies to automate manual claim processes, reduce cycle times, and improve accuracy in decision support.

Partner with Data Science to integrate advanced models, evaluate performance, and incorporate feedback loops for ongoing optimization.

Apply robust evaluation methods, agent tracing tools, and experimentation frameworks to validate improvements and refine system behavior.

Utilize Python extensively while contributing to frontend with React/Next.js components and data analysis to inform product decisions.

Work with data processing frameworks and tools such as Spark, Kafka, Airflow, and cloud provisioning environments to build resilient pipelines.

Communicate effectively with strong oral and written interpersonal skills across technical and non-technical audiences.

Requirements

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.

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.

Practical notes

Employment is at-will.

Location: Seattle, WA.

Engagement: Full-time.

Compensation: Base $183,000.00 - $251,000.00, Equity $41,250 - $70,000, Bonus 10.00%.

This role requires occasional travel.

Candidates must be authorized to work in the United States.

Role posted until filled.