Lead Agentic AI Architect: Production-Ready Solutions

Mapfre; Webster (MA); Hybrid; USD 140,000 - 205,000; Full time

Benefits offered by this job

PTO

401(k) & Profit Sharing

Medical, Dental, Vision Coverage

Other Benefits

Job summary

MAPFRE is seeking a hands-on Lead Agentic AI Solutions Architect to drive end-to-end AI solutions from discovery through deployment and continuous improvement. You will deliver production-ready agentic AI systems, mentor engineers, and shape the AI tools strategy across governance and platform teams.

The role requires 12+ years in software/ML/data engineering, 3+ years of production AI/LLM design, and strong Python and security expertise.

Qualifications

• Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related quantitative field with 12+ years of experience in software engineering, machine learning, or data engineering; or a Master’s degree with 10+ years of relevant experience.
• 3+ years designing and leading production AI/ML solutions, including at least 2 years with LLM-based applications and deploying multiple agentic systems into production.
• 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, with LangGraph strongly preferred, 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
• Proven 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
• 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, with the ability to explain technical concepts clearly, navigate competing priorities, influence without direct authority, provide technical direction, and mentor 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

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 right solution for the problem, determining when agentic AI, machine learning, rules‑based approaches, existing enterprise tools, or custom development provide the best balance 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 from prototyping through implementation, integration, testing, deployment, troubleshooting, and continuous improvement, writing production code and working alongside engineers.
• Provide technical direction, architecture and code reviews, and mentoring to Agentic AI Engineers while 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 that accelerate future AI delivery.
• Help shape the AI tools roadmap by evaluating capabilities such as Snowflake Cortex, Microsoft Copilot, models, platforms, and vendor solutions, and recommending build-versus-buy approaches.

Job description

MAPFRE is seeking a hands-on Lead Agentic AI Solutions Architect to drive end-to-end AI solutions from discovery through deployment and continuous improvement. You will deliver production-ready agentic AI systems, mentor engineers, and shape the AI tools strategy across governance and platform teams.

The role requires 12+ years in software/ML/data engineering, 3+ years of production AI/LLM design, and strong Python and security expertise.