Level

Shift TechnologyPosted 1w ago

Data Scientist/ Engineer (Hybrid -Boston)

Data Scientist/ Engineer (Hybrid -Boston) at Shift Technology scores 90 out of 100 on AI centrality, which makes it AI Level 4 of 4 (Builds AI) on this board. The level measures how much of the work is AI, not seniority.

Remote (US - Boston)mid$100k-$110k

AI in this role

Build and productionize LLM-based solutions, data pipelines, and agentic AI systems for insurance applications.

openaiclaudeanthropicgeminilangchainlanggraphcrewaimlflowdatabricksmcppython
prompt-engineeringragai-agentsai-evaluationmachine-learningllmdata-engineeringagentic-ai

Shift delivers AI agents that transform insurers' most critical work. By combining deep industry expertise and unmatched data resources, Shift provides proven results that have earned the trust of hundreds of the world's leading insurers. Our insurance-grade AI is accurate, explainable, and secure—empowering human experts to move with unmatched speed, total confidence, and a renewed focus on the people they serve.

 

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Our culture is built on innovation, trust, and a drive to transform the insurance industry through our SaaS platform. We come from more than 50 different countries and cultures and together we are creating the future of insurance.

Learn more at www.shift-technology.com

 

About the Team

  • This role is part of our Data Science team which is the largest team in our organization consisting of over 200+ Data Scientists throughout the world.
  • Our Data Scientists work in a full lifecycle role and on a broad range of subjects acquiring extensive technical and professional experience in data science, data engineering, coding, business understanding and client engagement.
  • Our company is small enough that each person’s achievements has an impact on our overall performance, yet big enough to be a world leader and innovator in our domain.
  • As a member of the data science team, you will be working alongside our technical experts and your role will be key to rolling out our enterprise level solutions to our clients.

Key Responsibilities

  • Your role will be to actively contribute to the US- Insurance roadmap and clients, and working on various data types such as structured data, free text, documents and images. 
  • Build and productionize data pipelines (structured, text, documents, images) optimized for LLMs and multi-modal models.
  • Design, develop and deploy LLM-based solutions (RAG, embeddings, instruction tuning) for subrogation, claims handling, document understanding, and related use cases.
  • Experiment with the latest in Agentic AI technologies (Langchain/Langgraph, OpenAI Agent SDK, MCP, A2A) and develop MVP for the next generation of autonomous subrogation solutions.
  • Develop "Chain-of-Thought" and "ReAct" prompting strategies to ensure the agent can justify its liability percentages based on the Comparative Negligence laws of different jurisdictions.
  • Create custom "tools" for the agent, allowing it to query internal databases, call external weather APIs, or calculate impact force based on telemetry data.
  • Establish rigorous evaluation frameworks (LLM-as-a-judge) to ensure the agent’s decisions are unbiased, legally sound, and explainable.
  • Ensure responsible-AI practices: privacy, hallucination mitigation, explainability and compliance.
  • Lead client workshops, present prototypes, gather feedback and help define roadmap priorities.

WHAT WE ARE LOOKING FOR

We are looking for candidates with diverse skills to help us build excellent technology solutions for our clients and be proficient in the following skills:

  • Expert proficiency in production-level object-oriented programming (OOP) for building scalable and reliable systems.
  • Proven hands-on experience with Large Language Models (LLMs) and generative AI techniques (including RAG, embeddings, prompt engineering, and model tuning), leveraging frameworks such as OpenAI/Anthropic or open-source variants.
  • Solid foundation in ML fundamentals with practical experience in the full machine learning lifecycle, including model evaluation, monitoring, versioning, and deployment in production environments.
  • Experience designing and implementing robust data pipelines for document, OCR, and multi-modal data workflows.
  • Agentic Frameworks: Experience with integrating frameworks like LangChain/LangGraph, OpenAI Agent SDK, CrewAI, A2A/MCP with Databricks or Azure-hosted models (e.g., DBRX, OpenAI GPT-5.3, Anthropic Claude, Google Gemini).
  • Demonstrated ability to effectively engage with clients, translate complex business needs into clear, actionable technical solutions, and manage stakeholder expectations.

 

Highly Desired Skills

  • Databricks Ecosystem: Deep expertise in Mosaic AI (formerly MosaicML), Unity Catalog, and Delta Lake.  Good understanding of Spark data architecture is a plus.
  • Experience using MLflow for the full lifecycle: from experiment tracking and prompt engineering in the AI Playground to model evaluation.

 

#LI-MG1   #LI-Hybrid

 

 

The range listed is for base compensation.  Your actual base salary will vary based on factors including location and individual qualifications objectively assessed during the interview process. 

In addition to base salary, your total rewards package will include additional components such as incentive pay and benefits.  If you're interviewing for this role, speak with your Talent Acquisition Partner to learn more about the specific details for this position.

Base Salary Pay Range$100,000—$110,000 USD

To support our permanent, full time employees at every stage of their careers and lives, we provide a competitive total rewards and benefits package. Here are the global benefits we’d like to highlight:

  • Flexible remote and hybrid working options
  • Competitive Salary and a variable component tied to personal and company performance
  • Multiple Learning and Development opportunities, including Focus Fridays, a half-day each month to focus on learning and personal growth
  • Generous PTO and paid holidays
  • Mental health benefits 
  • 2 MAD Days per year (Make A Difference Days for paid volunteering)

Additional benefits may be offered by country, based on your eligibility - ask your recruiter for more information. Intern and Apprentice positions may receive some of these benefits - ask your recruiter for more details.

AI tools are used to help review applications for this role. Read our AI in Recruitment Notice for what the AI considers, how to request a human review, and our most recent bias audit.

At Shift we strive to be a diverse and inclusive workforce. We welcome applications from and hire people who will contribute to the diversity of our company, without regard to race, color, religion, marital status, age, national or ethnic origin, physical or mental disability, medical condition, pregnancy, genetic information, gender identity or expression, sexual orientation, or other non-merit criteria. Shift Technology is committed to providing reasonable accommodations for qualified individuals with disabilities in our application and employment process. Should you require accommodation, please email [email protected] and we will work with you to meet your accessibility needs.

Please be aware of scammers and only trust correspondence that comes from emails ending in "shift-technology.com". We will never do initial outreach to you via Whatsapp/Text/SMS, never ask for banking information or personal identification numbers (ex. Social Security Number) as part of our recruitment process.

Shift Technology does not accept unsolicited CVs from recruiters or employment agencies in response to the Shift Technology Careers page or a Shift Technology social media post. Any unsolicited CVs, including those submitted directly to hiring managers, are deemed to be the property of Shift Technology.

Prepare for this job

A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.

Skills and AI tools this role asks for

Prompt EngineeringRagAI AgentsAI EvaluationMachine LearningLlmData EngineeringAgentic AI

Questions you could be asked

  1. How do you structure and test a prompt to get consistent output from a language model?
  2. How would you design a retrieval step so the model answers from real data instead of guessing?
  3. How do you decide when an AI agent can act on its own versus asking for approval first?
  4. How do you decide that one model's output is better than another's for a given task?
  5. Tell me about a project where machine learning was part of your work. What did you do?

Adapt your resume

  • List these exact terms on your resume: Prompt Engineering, Rag, AI Agents, AI Evaluation, and Machine Learning. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
  • Lead with what you built, trained or shipped — this role is judged on the AI system itself, not the tools around it.

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