Data Scientist/ Engineer (Hybrid -Boston)
About this role
Building enterprise-level insurance AI solutions involves developing LLM-based systems, designing data pipelines for multi-modal data, and experimenting with agentic technologies for subrogation and claims handling. This role sits within the Data Science team, a global group of over two hundred professionals who own the complete product lifecycle from data engineering to client engagement. Members of this team regularly lead client workshops, build custom agent tools, and establish rigorous evaluation frameworks to ensure decisions remain explainable and legally sound.
Candidates joining this team will shape the US insurance roadmap by collaborating closely with technical experts and enterprise clients. Success in this position requires a balance of production-level programming skills, practical generative AI experience, and the ability to translate complex business needs into technical solutions. Professionals who thrive here enjoy a hybrid work environment in Boston while making a tangible impact on autonomous SaaS platforms.
What you will do
- Contribute directly to the US insurance product roadmap by handling structured data, free text, documents, and images.
- Build and productionize scalable data pipelines optimized for large language models and multi-modal workflows.
- Design and deploy generative AI solutions including retrieval-augmented generation, embeddings, and instruction tuning for claims and subrogation use cases.
- Experiment with agentic technologies to develop minimum viable products for next-generation autonomous insurance solutions.
- Implement advanced prompting strategies such as chain-of-thought and ReAct to enable justified agent decisions.
- Establish rigorous evaluation frameworks using LLM-as-a-judge methodologies to maintain unbiased and explainable agent outputs.
- Lead client workshops, present technical prototypes, and gather feedback to refine ongoing roadmap priorities.
What you need
- Expert proficiency in production-level object-oriented programming for building scalable and reliable systems.
- Proven hands-on experience with large language models and generative AI techniques using commercial or open-source frameworks.
- Solid foundation in machine learning fundamentals covering the complete lifecycle from evaluation to production monitoring.
- Demonstrated experience designing robust data pipelines for document, OCR, and multi-modal data workflows.
- Practical integration experience with agentic frameworks such as LangChain, LangGraph, CrewAI, or OpenAI Agent SDK.
- Strong ability to engage directly with clients and translate business requirements into actionable technical solutions.
Nice to have
- Deep expertise in the Databricks ecosystem including Mosaic AI, Unity Catalog, and Delta Lake
- Familiarity with Spark data architecture
- Experience using MLflow for experiment tracking, prompt engineering, and model evaluation
Benefits
- Flexible remote and hybrid working options
- Competitive salary and a variable component tied to performance
- Multiple learning and development opportunities including Focus Fridays
- Generous PTO and paid holidays
- Mental health benefits
- Two MAD Days per year for paid volunteering
Skills and tech stack
Questions candidates ask
What is the work location policy for this job?
This position offers flexible remote and hybrid working options based out of Boston.
What is the salary range for this role?
The base compensation pay range is $100,000 to $110,000 USD, with actual base salary varying based on location and individual qualifications.
What tools and frameworks will I be working with?
You will work with agentic frameworks like LangChain, LangGraph, and OpenAI Agent SDK, alongside Databricks-hosted models and MLflow.
What team will I be joining?
This role is part of the Data Science team, which is the largest team in the organization with over 200 data scientists worldwide.
The application is on the official Shift Technology careers page.
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