Lead AI architecture and technical design workshops with internal teams and customers to shape PCAI’s applied and agentic AI strategy.
Define customer ready AI architectures for private and hybrid cloud – spanning models, runtimes, knowledge/semantic layers, security, governance, and observability.
Evaluate and select ISV partner technologies for the AI platform stack, develop TCO and roadmap options, and drive key architectural decisions for PCAI products and customer solutions.
Design multi ‑ agent, LLMOps / AgentOps , and AI security/governance blueprints, ensuring performant , reliable, and trustworthy AI systems.
Set the Architecture direction of AgentOps / LLMOps , AI Governance, AI Security, and AI Observability capabilities in PCAI offerings.
Build reusable AI components and agents and partner with engineering to take POCs into scalable, production ‑ grade services.
Troubleshoot and optimize AI systems at scale and establish best practices for model lifecycle , evaluation, and responsible AI.
Recommend design optimizations and improvements for performance, cost efficiency, reliability, and trustworthiness.
Create and present high‑impact technical content (reference architectures, design patterns, whitepapers, conference talks, and internal/external publications) to influence customers, partners, and internal stakeholders.
Mentor senior engineers and architects and provide technical leadership across engineering, applied science, and field organizations.

Requirements

Bachelor's degree in computer science or relevant field
At least 15+ years of progressive technical leadership and architectural experience.
Minimum of 2 years of experience designing and implementing scaled Agentic AI and Generative AI solutions that are in production/operations.
Minimum of 2 years of experience designing and implementing agentic AI and Generative AI platforms and frameworks that are used by multiple AI solutions, products, or teams.
Minimum of 5 years of experience designing, engineering, and operationalizing large‑scale AI/ML solutions on at least one large public cloud platform, using: Cloud‑native AI services and frameworks, open‑source technologies, and third‑party tools (e.g., observability, security, governance, data/feature platforms).
Minimum of 5 years of expert-level understanding of key AI technologies from public cloud providers, open source ecosystems, and third‑party vendors.
Hands ‑ on experience with: Foundation models and large language models (LLMs).
Building and optimizing RAG pipelines, multi‑agent systems, and tool‑using agents.
Architecting knowledge graphs and semantic layers to support AI agents and domain‑specific reasoning.
Implementing AI security, governance, and observability in production environments.
Strong understanding of cloud‑native architectures (containers, microservices, Kubernetes, service meshes) and hybrid/private cloud patterns.

Benefits

Health & Wellbeing
Personal & Professional Development
Unconditional Inclusion

Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools

AI architectureAgentic AIGenerative AIAI securityAI governanceAI observabilitylarge-scale AI/ML solutionscloud-native AI servicesfoundation modelslarge language models

Soft Skills

technical leadershipmentoringcommunicationinfluencingtroubleshootingoptimizingdesigningpresenting