Head of AI Platform Engineering - Execution Plane

About this role

As the Head of AI Platform Engineering – Execution Plane, you will lead the development and implementation of our enterprise platform’s execution layer including management of agentic AI workloads, model gateways, agent runtimes, tool/action gateways, MCP servers, orchestration frameworks, or AI execution engines.

You will: You will collaborate closely with cross-functional teams, stakeholders, and technology partners to develop and integrate automation solutions that drive business growth, improve customer experiences, and reduce operational costs.

You have: • Bachelor’s or master’s degree in computer science, engineering, management or a related field. • Strong people leadership experience managing software engineering teams, including hiring, coaching, performance management, and developing senior technical talent. • Deep hands-on technical background designing, building, and operating production-grade distributed systems, AI/ML platforms, data platforms, or cloud-native runtime services. • Experience leading teams responsible for the execution layer of a platform, including runtime services, model inference, retrieval, orchestration, tool invocation, workflow execution, or production AI operations. • Ability to own the roadmap and delivery for execution plane capabilities such as model gateways, agent runtimes, tool/action gateways, runtime adapters, MCP services, knowledge bases, retrieval pipelines, inference services, and deployment patterns. • Strong understanding of data access patterns, enterprise APIs, retrieval-augmented generation, embeddings, vector/search systems, context engineering, and governed access to systems of record. • Experience building reliable, scalable, low-latency execution services with clear contracts, strong observability, graceful degradation, retry patterns, rate limits, and operational resilience. • Ability to partner with control plane, developer experience, data engineering, security, architecture, operations, and domain application teams to ensure execution technologies operate behind governed platform interfaces. • Proven ability to drive engineering excellence through design reviews, architecture standards, testing, CI/CD, infrastructure automation, incident response, SLOs, runbooks, and production support mechanisms. • Strong understanding of enterprise security and compliance requirements for runtime execution, including identity propagation, auditability, data handling, least privilege access, secrets management, and environment isolation. • Strong communication and influence skills, with the ability to simplify complex runtime, data, and AI execution topics for senior stakeholders while aligning teams around reusable platform patterns.

You will: • Experience with agentic AI systems, LLM platforms, model gateways, agent runtimes, tool/action gateways, MCP servers, orchestration frameworks, or AI execution engines. • Experience with AWS-based AI execution services and cloud-native patterns, including Bedrock, AgentCore, SageMaker, Lambda, Step Functions, API Gateway, EKS, DynamoDB, S3, IAM, CloudWatch, and related DevOps tooling. • Familiarity with RAG systems, enterprise search, vector databases, embedding models, rerankers, knowledge bases, context engineering, and governed retrieval from enterprise data sources. • Experience designing multi-tenant runtime platforms with environment isolation, workload identities, RBAC/ABAC, cross-account access patterns, quotas, throttling, and secure service-to-service communication. • Background in MLOps, LLMOps, AIOps, model lifecycle management, evaluation pipelines, model serving, inference optimization, or production AI operations. • Experience with observability for AI workloads, including distributed tracing, token usage, latency, model/tool errors, cost attribution, quality metrics, safety metrics, and operational dashboards. • Experience with performance, scalability, and cost optimization for high-volume runtime services, including caching, batching, streaming, load testing, capacity planning, and GPU/CPU optimization where applicable. • Experience building reusable platform abstractions, SDKs, runtime adapters, reference architectures, or deployment templates that make execution technologies portable across vendors and use cases. • Experience integrating enterprise tools, APIs, data services, and workflow systems through governed connectors rather than point-to-point application wiring. • Comfort operating in a regulated, matrixed environment where production safety, auditability, resiliency, and vendor optionality are core design principles.

Location: • New York, New Jersey or Pennsylvania

• Up to 10% travel within US

Our promise: •  At Guardian, you’ll have the support and flexibility to achieve your professional and personal goals. •  Through skill-building, leadership development and philanthropic opportunities, we provide opportunities to build communities and grow your career, surrounded by diverse colleagues with high ethical standards

We offer: • Meaningful and challenging work opportunities to accelerate technology and innovation in a secure and compliant way • Competitive compensation • Excellent medical, dental, supplemental health, life and vision coverage for you and your dependents with no wait period • Life and disability insurance • A great 401(k) with match • Tuition assistance, paid parental leave and backup family care • Dynamic, modern work environments that promote collaboration and creativity • Flexible time off, dress code, and work location policies to balance your work and life in the ways that suit you best • Social responsibility in all aspects of our work. We volunteer within our local communities, create educational alliances with colleges, drive a variety of initiatives in sustainability, and advocate for diversity and inclusion in all that we do.

About Guardian: Every day, Guardian provides Americans the security they deserve through our insurance and wealth

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