VP of Cloud Engineering, Operations & Delivery

VP of Cloud Engineering, Operations & Delivery

Job Type:
Full-Time | Executive Leadership

Location: Remote

Salary: $200k - $225k base salary, plus bonus and equity
About the Role

We are seeking an experienced and well-rounded
VP of Cloud Engineering, Operations & Delivery
to lead our cloud practice across a diverse portfolio of industry verticals. This role sits at the intersection of
technical authority, executive leadership, and forward-thinking innovation
— someone who brings genuine cloud engineering depth, while also driving strategy, client relationships, and organizational growth.

You will lead high-performing teams delivering complex, multi-cloud solutions across
AWS, Azure, and Google Cloud Platform
, setting the technical bar while ensuring the business delivers on its commitments. Critically, you will help shape and lead our evolution into an
agentic AI-powered future
— identifying opportunities to transform how our teams and our clients design, deploy, operate, and optimize cloud infrastructure using AI agents and intelligent automation.

The ideal candidate is a natural communicator who can shift seamlessly from an architecture discussion with engineers to a strategic briefing with a client's executive team — and be credible in both rooms. They are also someone who looks at today's manual, repetitive, or complex processes and asks:
"How do we let intelligent agents handle this?"

Key Responsibilities

Technical Leadership
• Serve as the senior technical authority for cloud architecture and infrastructure decisions across AWS, Azure, and GCP
• Advance and mature our
Infrastructure as Code (IaC)practices — Github, Jenkins, Terraform, Qualys, Sonarqube, etc. — ensuring consistency, security, and scalability across client environments
• Provide meaningful technical guidance and architectural direction to engineering teams — going beyond high-level oversight to engage substantively on design decisions, standards, and delivery quality
• Guide adoption of cloud-native patterns including Kubernetes (EKS/AKS/GKE), serverless, CI/CD automation, and event-driven architecture
• Lead architecture reviews and serve as the escalation point for complex technical challenges
• Ensure security and compliance are embedded into infrastructure from the ground up — spanning IAM design, network segmentation, secrets management, and frameworks such as SOC 2, NIST, CIS, HIPAA, and PCI-DSS

Agentic AI Strategy & Transformation
• Champion the adoption of
AI agents and multi-agent systemsto transform how cloud infrastructure is built, operated, and optimized — moving teams from reactive, manual workflows to intelligent, autonomous execution
• Identify high-value opportunities to introduce agentic workflows into engineering operations — including infrastructure provisioning, incident detection and remediation, cost optimization, compliance monitoring, security response, and deployment pipelines
• Lead the evaluation and adoption of agentic AI frameworks and platforms (e.g., LangGraph, AutoGen, Amazon Bedrock Agents, Azure AI Agent Service, Vertex AI Agent Builder) to build purpose-built agents that extend the capabilities of our engineering teams
• Define governance, guardrails, and human-in-the-loop checkpoints for agentic systems operating in cloud environments — ensuring autonomous actions are safe, auditable, and aligned with client expectations
• Collaborate with engineering and solutions teams to design
agentic delivery pipelines— where AI agents assist in code generation, IaC validation, drift detection, security scanning, and release orchestration
• Work with peer technology teams to identify process transformation opportunities — helping envision, roadmap and execute an agentic future state for cloud operations and engineering workflows
• Stay ahead of the rapidly evolving AI agent ecosystem and bring informed, practical perspectives on what is production-ready versus experimental

Operations & Reliability
• Own the operational health of cloud environments across the client portfolio — including availability, performance, security posture, and cost efficiency
• Mature SRE practices across the organization: SLOs, error budgets, incident management, and blameless postmortems
• Drive FinOps discipline — optimizing cloud spend through right-sizing, commitment strategies, tagging governance, and anomaly detection — increasingly augmented by AI-driven insights and autonomous recommendations
• Define and enforce observability standards across logging, metrics, and

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