AI Engineer (Hybrid)

Motion Recruitment; Webster (MA); Hybrid; USD 150,000 - 210,000; Full time

Job summary

MAPFRE is seeking an Agentic AI Engineer for a full-time hybrid role based in Boston or Webster, MA, focusing on developing agentic AI solutions, LLM-powered applications, and enterprise AI services using Python, LangGraph, AWS, and modern cloud technologies.

This role involves collaborating with AI architects, business stakeholders, and domain experts to deliver production-ready AI solutions from prototype to production, establishing engineering patterns for agentic AI, and shaping AI adoption

Qualifications

• 7+ years of software engineering, ML, or data engineering experience
• 2+ years building LLM-based applications including at least one production-deployed agentic system
• Strong Python development experience and software engineering fundamentals
• Experience building APIs, integrating tools and services, automated testing, version control, debugging, and error handling
• Hands-on experience with agent frameworks or SDKs, LangGraph strongly preferred
• Experience using major model APIs or managed AI platforms such as Amazon Bedrock
• Experience building production AI agents integrating with enterprise systems, APIs, and tools
• Experience evaluating LLM applications and agents using test datasets, metrics, regression testing, and model-based evaluators
• Understanding of AI agent reliability, security risks, governance requirements, and responsible AI practices
• Strong communication skills and ability to explain AI behaviors to stakeholders
• Proven ability to solve complex, ambiguous problems independently and deliver results

Responsibilities

• Designing, building, and deploying AI agents and multi-step agentic workflows
• Developing Python-based backend services, APIs, and enterprise integrations
• Implementing cloud-native AI solutions using AWS, containers, and CI/CD practices
• Building evaluation frameworks, observability, monitoring, and governance controls
• Integrating AI agents with enterprise systems, data sources, APIs and MCP services
• Design and deliver agentic AI solutions that improve underwriting, claims, and other insurance workflows
• Translate solution designs into production-ready AI services and applications
• Build secure, resilient backend services with testing, monitoring, and audit capabilities
• Create evaluation datasets, automate testing, and continuously improve agent performance
• Implement guardrails, human-in-the-loop workflows, and governance controls
• Collaborate with architects, product owners, business stakeholders, and technical teams to prototype, deploy, and scale AI solutions
• Measure technical performance and business value while communicating outcomes and limitations to stakeholders

Skills

LLM-based applications

Python

API development

Agent frameworks

LangGraph

AWS

Production AI agents

Testing

Security & governance

Communication

Problem solving

Education

Bachelor's degree in Computer Science, Engineering, or related quantitative field

Master's degree in a related field

Tools

LangGraph

AWS

Python

APIs

Job description

Join MAPFRE as an Agentic AI Engineer and help build production-grade AI agents that transform complex insurance workflows at scale. This is a full-time hybrid opportunity based in Boston or Webster, Massachusetts, focused on developing agentic AI solutions, LLM-powered applications, and enterprise AI services using Python, LangGraph, AWS, and modern cloud technologies.

This is an opportunity to work at the intersection of artificial intelligence, software engineering, and insurance while owning solutions from prototype through production. You'll collaborate directly with AI architects, business stakeholders, and domain experts to deliver measurable business impact, establish engineering patterns for agentic AI, and help shape the future of AI adoption across a global insurance organization.

Required Skills & Experience

• Bachelor's degree in Computer Science, Engineering, or related quantitative field with 7+ years of software engineering, machine learning, or data engineering experience, or Master's degree with 5+ years of relevant experience
• 2+ years of hands-on experience building LLM-based applications, including at least one production-deployed agentic system used by real users
• Strong Python development experience and software engineering fundamentals
• Experience building APIs, integrating tools and services, automated testing, version control, debugging, and error handling
• Hands-on experience with agent frameworks or SDKs, with LangGraph strongly preferred
• Experience using major model APIs or managed AI platforms such as Amazon Bedrock
• Experience building production AI agents that integrate with enterprise systems, APIs, and tools
• Experience evaluating LLM applications and agents using test datasets, metrics, regression testing, and model-based evaluators
• Understanding of AI agent reliability, security risks, governance requirements, and responsible AI practices
• Strong communication skills and the ability to explain AI behaviors and limitations to technical and non-technical stakeholders
• Proven ability to solve complex, ambiguous problems independently and deliver results

Desired Skills & Experience

• Insurance industry experience preferred
• Claims or underwriting expertise strongly preferred
• Experience deploying AI applications to AWS cloud environments
• Experience with containerization and CI/CD pipelines
• Experience with retrieval-augmented generation (RAG), context engineering, and structured outputs
• Experience integrating agents with enterprise systems through APIs and MCP servers
• Experience mentoring team members and establishing engineering best practices across teams

What You Will Be Doing

Tech Breakdown

• Designing, building, and deploying AI agents and multi-step agentic workflows
• Developing Python-based backend services, APIs, and enterprise integrations
• Implementing cloud-native AI solutions using AWS, containers, and CI/CD practices
• Building evaluation frameworks, observability, monitoring, and governance controls
• Integrating AI agents with enterprise systems, data sources, APIs and MCP services

Daily Responsibilities

• Design and deliver agentic AI solutions that improve underwriting, claims, and other insurance workflows
• Translate solution designs into production-ready AI services and applications
• Build secure, resilient backend services with testing, monitoring, and audit capabilities
• Create evaluation datasets, automate testing, and continuously improve agent performance
• Implement guardrails, human-in-the-loop workflows, and governance controls
• Collaborate with architects, product owners, business stakeholders, and technical teams to prototype, deploy, and scale AI solutions
• Measure technical performance and business value while communicating outcomes and limitations to stakeholder

Posted By: Matthew Power