**This position follows our hybrid workstyle policy: Expected to be in a Raymond James office location a minimum of 10-12 days a month.** **_Please note: This role is not eligible for Work Visa sponsorship, either currently or in the future._** **Technical Skills/Experience:** Leadership of High-Performing Technical Teams Proven ability to recruit, develop, and lead elite engineering, AI/ML, and platform teams with deep expertise in agentic systems, orchestration, and cloud-native architectures. Establishes a culture of precision, accountability, and high reliability—balancing innovation with disciplined engineering suitable for regulated financial environments. Creates clear technical strategy, operating models, reference architectures, and quality gates that scale across teams and programs. Demonstrated success driving organizations that excel at both deep technical R&D and production excellence (observability, reliability, resilience, scalability). Strong communicator capable of translating complex system behaviors into clear decisions, tradeoffs, and roadmaps for senior leadership. **Agentic AI (Expert-Level) :** + Deep mastery of agentic AI architectures, reasoning loops, decision graphs, planning/critique patterns, and autonomous execution models. + Expert in context engineering, including hierarchical context flows, dynamic context construction, scoped memory, retrieval strategies, and minimizing cognitive overload. + Advanced capability designing orchestration patterns such as multi-agent collaboration, hierarchical agents, planning-directed tool use, and hybrid autonomous workflows. + Strong command of memory strategies including short-term (scratchpads, ephemeral state, execution frames) and long-term (vector stores, episodic memory, structured knowledge graphs). + Expertise in resiliency engineering for agentic systems, including fallback paths, redundancy, guardrails, validation layers, cross-agent voting, circuit breakers, and deterministic replay. + Hands-on experience with major agentic frameworks and realistic understanding of their strengths and weaknesses. **AWS** + Expertise designing scalable, resilient, and secure agentic systems on AWS. Proficiency across compute (ECS, EKS, Lambda, EC2), data services (DynamoDB, Aurora, S3, OpenSearch), and orchestration technologies (Step Functions, EventBridge, SQS, SNS). + Advanced experience with AI/ML services: Bedrock (Claude, Llama, Titan), SageMaker, Kendra, and hybrid retrieval architectures. + Strong grounding in IAM, VPC architecture, security controls, encryption (KMS), Secrets Manager, and WAF. + Mastery of observability: CloudWatch, X-Ray, structured logs, distributed tracing, performance tuning, autoscaling, and cost optimization under Well-Architected principles. **AI/ML & Software Engineering:** + Deep understanding of LLM behavior, tool-use patterns, structured output, evaluation frameworks, and safety/guardrail systems. + Experience designing AI systems aligned with regulatory, compliance, supervisory, and model-risk requirements in financial services.(Desired) + Proficiency in microservices, distributed systems, CI/CD automation, automated testing and canary/ring deployments. + Demonstrated ability to drive teams to deliver highly reliable, scalable, and secure production AI systems with clear SLAs and operational metrics. **Leadership & Execution:** + Ability to define and execute the enterprise roadmap for agentic AI, including reference architectures, governance patterns, best practices, and capability maturity models. + Skilled at leading organizations through R&D innovation cycles and production hardening cycles, ensuring prototypes evolve into durable enterprise services. + Strong track record partnering across business and technology stakeholders to deliver measurable value through safe, compliant deployment of advanced AI capabilities.