Agentic AI Engineer (Insurance & Agentic Workflows) Hybrid Boston or Webster Massachusetts
At a glance
Mid-level AI Engineering role at MAPFRE. Webster · $140,000–$191,000 base.
aimlroles summary, based on the employer's posting.
What you'll do
- Build and deploy agents for insurance work such as underwriting and claims, creating reusable components for future workflows
- Turn designs from the AI architect and product owner into working agents, weighing technical feasibility, cost and reliability
- Develop agents as backend services with secure APIs, testing, resilient error handling and links to enterprise systems and data
- Set agent success measures, evaluate results, investigate failures and improve performance over time
- Add human review points, action limits, monitoring and audit records, then prototype, deploy and explain results to stakeholders
What you bring
- A computer science, engineering or related quantitative degree, plus seven years of relevant experience, or a master's degree and five years
- At least two years building LLM applications, including a production agentic system used by real users
- Strong Python and software engineering skills across APIs, testing, error handling, version control and debugging
- Production experience with an agent framework or SDK and major model APIs or a managed AI platform; LangGraph is preferred
Who this fits
This mid-level, hands-on engineering role suits someone who can take agent systems from prototypes into production and work with both business and technical teams. The role is hybrid in Boston or Webster, Massachusetts. Insurance experience is preferred, particularly in claims or underwriting.
From the employer
Agentic AI Engineer (Insurance & Agentic Workflows) Hybrid, Boston or Webster
Summary
Are you excited about building AI systems that solve real-world problems at scale?
We are looking for a hands-on engineer to design, build, and ship production-grade AI agents that transform complex, high-impact insurance workflows. You will own solutions end to end, from early prototypes to reliable production systems, and help define how agentic AI is engineered and scaled across the organization. Working at the intersection of AI, software engineering, and insurance, you will tackle real business problems, collaborate directly with technical and domain experts, and see the measurable impact of what you build.
This role requires strong software engineering depth in Python, and practical experience building LLM-based and agentic systems. Experience in insurance or another regulated industry is a big plus.
What You’ll Do
- Design, build, and deploy AI agents and multi-step agentic workflows that transform high-impact complex insurance processes such as underwriting, and claims, creating reusable components and engineering patterns that accelerate future solutions
- Translate business and solution designs defined with the AI architect/product owner into working agents, advising on the technical feasibility, cost, and reliability trade-offs between deterministic rules, traditional ML, plain GenAI, and autonomous agents
- Build agents as well-defined backend services (e.g., FastAPI) with stable API contracts, secure authentication, resilient error handling, and automated testing, integrating them with enterprise systems, data sources, and APIs through tools and MCP servers
- Own agent quality and continuous improvement by defining success criteria, building test datasets and automated evaluations, diagnosing failures, and implementing targeted improvements
- Implement guardrails, human-in-the-loop checkpoints, action limits, observability, monitoring performance, reliability, cost control, and audit logging in line with AI governance and regulatory requirements
- Work directly with business and technical teams to rapidly prototype (building lightweight MVP interfaces (e.g., Streamlit)), validate, deploy, and scale solutions using cloud, containerization, and CI/CD practices.
- Measure technical performance and business value and communicate results and limitations to technical and non-technical stakeholders.
Required skills
- Bachelor’s degree in Computer Science, Engineering, or a related quantitative field, with either 7+ years of software, machine learning, or data engineering experience, or a Master’s degree with 5+ years of relevant experience
- 2+ years of hands-on experience building LLM-based applications, including at least one agentic system (tool calling, multi-step workflows, etc.) deployed to production and used by real users
- Strong Python skills and solid software engineering fundamentals, including API and tool integration, automated testing, error handling, version control, and debugging of non-deterministic systems
- Hands-on experience with at least one agent framework or SDK (LangGraph strongly preferred) and with major model APIs or managed AI platform such as Amazon Bedrock, building production AI agents that integrate with tools, APIs, and enterprise systems.
- Experience evaluating LLM applications or agents, including test datasets, metrics, regression testing, and appropriate use of model-based evaluators.
- Understanding of agent reliability and security risks, combined with pragmatic judgment, strong problem-solving skills, and the ability to determine where an agentic approach is, and is not, appropriate, communicating effectively with technical and business stakeholders. Proven ability to solve ambiguous, complex problems with minimal direction and high autonomy, with a results-driven mindset and the persistence to find root causes
- Strong communication skills, with the ability to work closely with architects and business experts and explain agent behavior and limitations to non-technical stakeholders
Desired skills
- Insurance domain knowledge is highly preferred, with claims or underwriting experience a strong plus
- Experience deploying production AI applications to the cloud, with AWS preferred, using containers and CI/CD
- Experience with retrieval-augmented generation (RAG), context engineering, and structured outputs, and with integrating agents into enterprise systems via APIs and MCP
- Experience mentoring team members and influencing best practices across teams
Why Mapfre?
As a global insurance leader with a strong local presence, we offer more than a job- we provide a purpose-driven career where your growth, well-being, and impact truly matter.
Purpose & Culture: Join a company built on trust, collaboration, and inclusion. Our values guide everything we do, creating a workplace where people feel respected and empowered.
Career Growth: Advance your skills through tuition reimbursement, leadership programs, and internal mobility opportunities. Your development is our priority.
Social Responsibility: Contribute to meaningful initiatives through Fundación Mapfre, supporting communities and sustainability worldwide.
Pay Transparency: The typical starting salary range for this role is determined by several factors including skills, experience, education, certifications, and location. Some roles at Mapfre are eligible for commission and/or bonus earnings, in addition to salary, calculated based upon factors set forth in the compensation plan for the role.
Salary Range: $140,000- $191,000
Benefits Highlights:
At Mapfre, we invest in our employees' well-being by offering a comprehensive benefits package, including:
- Paid Time Off (PTO): A flexible PTO program that combines vacation, personal, volunteer and sick time into one convenient bank of paid time off.
- 401(k) & Profit Sharing: Eligible employees may participate in Mapfre's 401(k) plan that includes company matching contributions up to certain amounts under the terms of the plan.
- Medical, Dental and Vision Coverage: Choice of comprehensive medical, dental and vision insurance coverage under group plans offered by the company.
- Other Benefits Include: STD, LTD, Life Insurance, FSA, HSA and various wellness programs
Benefits provided are subject to the terms and conditions of the applicable benefit plan or policy. The Company reserves the right to alter, amend, or terminate benefits in its sole discretion. To learn more about our benefit offerings please visit: https://mapfre.gobenefits.net/
If you require a reasonable accommodation during the application or selection process, please contact the Mapfre Talent Acquisition team at talentacquisition@mapfre.com. Mapfre is proud to be an Equal Opportunity Employer.
Important Notice:
The information above is intended to provide a general overview of available benefits. Eligibility, plan provisions, and coverage are governed by the terms and conditions of the applicable benefit plans and policies, which may be modified from time to time