Lead AI Solutions Architect - Agentic AI (Hybrid Boston or Webster)

MAPFRE • Webster, MA

7d • $140,000 - $205,000 • Hybrid

About The Position

Mapfre is seeking a hands-on Lead Agentic AI Solutions Architect to translate complex business needs into high-impact, production-ready Agentic AI solutions. The role partners with business leaders and domain experts to identify opportunities for AI and leads solutions from discovery through deployment and continuous improvement.

This is a lead individual-contributor role with end-to-end delivery accountability. The architect contributes production code, solves complex technical challenges, provides technical direction to Agentic AI Engineers, and partners across business, technology, data, governance, and platform teams. The role also helps shape the broader AI tools strategy, evaluating when enterprise capabilities, integrations, low-code/no-code solutions, or custom development are appropriate.

Success requires technical depth, delivery leadership, stakeholder engagement, and business judgment. The role brings structure to ambiguity, builds cross-functional partnerships, and keeps teams focused on measurable outcomes. Insurance or regulated-industry experience is a plus.

Requirements

• Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related quantitative field and 12+ years of experience in software engineering, machine learning, or data engineering; alternatively, a Master’s degree and 10+ years of relevant experience.
• 3+ years designing and leading production AI/ML solutions, including at least 2 years with LLM-based applications and experience deploying multiple agentic systems into production for real users.
• Strong hands-on Python and software engineering expertise, including designing, building, integrating, testing, deploying, and troubleshooting production AI solutions; API and tool integration; automated testing; error handling; version control; code review; and debugging non-deterministic systems.
• Deep practical knowledge of agentic architectures and patterns, including tool calling, multi-agent orchestration, MCP, A2A or similar agent interoperability approaches, RAG, context and state management, structured outputs, and human-in-the-loop workflows.
• Hands-on experience with an agent framework or SDK and major model APIs or managed AI platforms such as Amazon Bedrock.
• Strong architecture and production-engineering fundamentals, including API design, enterprise integration, authentication and authorization, security, cloud architecture and deployment, containers, CI/CD, observability, resilience, scalability, and cost trade-offs.
• Experience defining AI evaluation and production-readiness strategies, including test datasets, metrics, regression and adversarial testing, model-based evaluators, reliability, security, AI governance, and regulatory requirements.
• Ability to translate business processes into practical technical solutions and determine when agentic AI, enterprise tools, platform-native capabilities, low-code/no-code solutions, or custom development are appropriate based on business needs, readiness, governance, risk, and cost.
• Demonstrated ownership of complex, cross-functional solutions from discovery through production, including scope, milestones, dependencies, risks, adoption, and operational transition.
• Strong communication, stakeholder management, and executive-level presentation skills, including explaining technical concepts clearly, navigating competing priorities, influencing without direct authority, providing technical direction, and mentoring engineers.
• Strategic and pragmatic business judgment, with a track record of turning business priorities into achievable technology solutions while balancing technical rigor, simplicity, speed, cost, risk, and operational needs.

Nice To Haves

• Experience in property and casualty insurance, particularly underwriting or claims, or delivering AI solutions within another highly regulated industry.
• Experience with process mapping, workflow redesign, organizational adoption, and measurement of operational business outcomes.
• Hands-on experience with semantic layers, ontologies, knowledge graphs, or graph-based retrieval in production AI or analytics solutions.
• Experience with Snowflake Cortex or comparable analytics, AI, and business productivity platforms.
• Experience with LangGraph; it is strongly preferred.
• AWS experience is preferred.

Responsibilities

• Lead AI solutions from concept through production, translating business objectives into scope, priorities, milestones, and phased releases while managing dependencies, risks, blockers, deployment, and operational handoff.
• Partner with business and domain experts to understand and redesign insurance workflows, assess data, knowledge, integration, and process readiness, and identify prerequisites for successful delivery.
• Recommend the appropriate solution approach, considering agentic AI, machine learning, rules-based approaches, enterprise tools, or custom development in light of value, reliability, cost, risk, and human judgment.
• Architect secure, production-ready agentic AI solutions, including orchestration, tool and data integrations, context and state management, execution boundaries, recovery and fallback mechanisms, and human oversight.
• Remain hands-on through prototyping, implementation, integration, testing, deployment, troubleshooting, and continuous improvement; write production code and work alongside engineers.
• Provide technical direction, architecture and code reviews, and mentoring to Agentic AI Engineers, partnering with their managers to align priorities and capacity.
• Define success measures, acceptance criteria, evaluation strategies, and production-readiness standards, including failure, adversarial, and regression testing.
• Partner with data architecture and governance teams to apply semantic models and domain context while aligning definitions, entities, relationships, and rules with enterprise standards.
• Embed security, responsible AI, governance, and regulatory controls into solutions, including access controls, guardrails, action limits, monitoring, and auditability.
• Coordinate rollout, business readiness, operational support, and continuous improvement while developing reusable patterns to accelerate future AI delivery.
• Help shape the AI tools roadmap by evaluating Snowflake Cortex, Microsoft Copilot, models, platforms, and vendor solutions, and recommending build-versus-buy approaches.

Benefits

• Flexible paid time off combining vacation, personal, volunteer, and sick time.
• 401(k) plan with company matching contributions, subject to plan terms.
• Profit sharing.
• Medical insurance coverage.
• Dental insurance coverage.
• Vision insurance coverage.
• Short-term disability insurance.
• Long-term disability insurance.
• Life insurance.
• Flexible spending account (FSA).
• Health savings account (HSA).
• Wellness programs.
• Tuition reimbursement.
• Leadership programs and internal mobility opportunities.

What This Job Offers

• Job Type: Full-time
• Career Level: Senior