This manager-level position is responsible for people management and sales enablement. May also be responsible for project oversight of staff augmentation projects.

Required experience and qualifications

• 15+ years of experience in infrastructure architecture, cloud engineering, or platform consulting, with proven ownership of end-to-end architecture and delivery.
• Strong fundamentals in networking, operating systems, distributed systems, and enterprise security.
• Proven experience delivering secure, highly available platforms in regulated or enterprise environments.
• Deep hands-on experience with:
  • Cloud infrastructure (OCI preferred AWS/Azure/GCP acceptable)
  • Enterprise network design (VPC/VCN, VPNs, routing, firewalls, proxies, private endpoints, DNS)
  • Kubernetes/container platforms (OKE/EKS/AKS/GKE), secure cluster patterns, and scaling strategies
  • Infrastructure-as-Code (Terraform strongly preferred) and automation (Python/shell)
  • Observability stacks (logs/metrics/traces) and integration with enterprise monitoring tools
  • IAM, vault/key management, secrets handling, encryption standards, and audit controls
• Strong customer-facing skills: requirements discovery, architecture documentation, and delivery leadership.

Preferred (nice-to-have) skills

• LLM inference serving (open models and/or managed endpoints), multi-model routing, and AI workload isolation.
• GPU platform engineering: scheduling, node pool design, performance tuning, and cost controls.
• Experience implementing agentic AI runtime patterns with safe tool execution and enterprise guardrails.
• Hybrid and multi-cloud deployments, including on-prem connectivity and enterprise integration patterns.
• Familiarity with data platforms relevant to AI (vector stores, metadata stores, object storage patterns).

Core competencies (what we value)

• Systems thinking and security-first architecture mindset
• Strong problem solving in constrained enterprise environments
• Crisp documentation and executive-ready communication
• Hands-on delivery orientation (not just advisory)
• Ownership, urgency, and accountability for production outcomes

Scope and impact (IC4/M3 expectations)

• Independently leads complex customer AI infrastructure programs from discovery through production and handover.
• Unblocks security/network constraints and drives approvals with clear evidence and mitigations.
• Establishes reusable, referenceable blueprints (secure AI landing zones, LLM hosting patterns, DR templates, observability baselines).
• Raises the quality bar by mentoring teams and institutionalizing guardrails, reliability practices, and delivery accelerators.
• Excellent leadership, communication, and stakeholder management skills.
• Manage a small team of AI consultants

Ensures that operational policies are followed and that business objectives are achieved by focusing on best practices and process improvements. Responsible for operational metrics and business results for assigned area of responsibility. Typically manages individual contributors and/or entry-level managers. Monitors consultant activities and performance on projects (e.g. read status reports, respond to staffing and availability issues, pro-actively seek out project performance reviews, etc.). May serve as project advisor for moderately complex engagements.

Career Level - M3