Manager, AI and Cloud Solutions

Dragos • United States • 1w ago

About the Role:

Dragos is looking for a hands-on technical leader to own two of our complimentary workstreams: enterprise cloud infrastructure management and internal AI delivery. As a Manager, AI and Cloud Solutions on our IT team, you'll take prioritized business problems and turn them into reliable, secure, and scalable production services — while building and guiding a small team of cloud and AI engineers. Your scope spans cloud operations across AWS and Azure (architecture, security, cost, and reliability) and AI enablement (deploying AI-powered applications, integrating copilots and agents into enterprise systems, and making them production-ready). This is a hands-on builder and team leadership role for someone who thrives on turning real business problems into durable, scalable technology while also growing and guiding a small team of cloud and AI engineers.

Responsibilities:

Implement and manage AI-powered tools, copilots, and workflow automations from POC to production, owning the full technical lifecycle including integrations with enterprise systems via APIs, webhooks, MCP servers, and core SaaS tooling.
Design, deploy, and maintain cloud infrastructure on AWS and Azure, including IAM, VPCs, security groups, multi-account strategies, and cost optimization through Savings Plans and resource right-sizing.
Prioritize capabilities already available in the existing tech stack and design targeted, scalable services only when genuine gaps exist.
Own reliability, observability, and security controls across all AI and cloud services, including incident response, debugging complex multi-service environments, and driving continuous improvement in partnership with the Security team.
Instrument solutions, collect adoption metrics and user feedback, and iterate based on real-world usage and business outcomes.
Supervise and mentor a team of cloud and AI engineers and contractors through 1:1s, technical guidance, work planning, sprint prioritization, and professional development.
Set clear expectations, provide ongoing feedback, conduct performance reviews, and contribute to hiring decisions for the cloud and AI engineering team.

Qualifications:

3+ years of software or systems engineering experience delivering internal tools or services end-to-end (design, build, deploy, operate), including at least 1 year supervising or leading technical staff.
Demonstrated expertise with AWS and Azure core infrastructure services, including serverless and data services, with the ability to architect and operate production workloads and select the right service for a given use case.
Experience with AWS and Azure cost management practices, including Cost Explorer, Budgets, and tagging strategies to maintain visibility and control over cloud spend.
Experience building LLM-based applications and enterprise integrations, including APIs, MCPs, automation frameworks, and workflow orchestration.
Working knowledge of practical AI implementation patterns including embeddings, retrieval, prompt engineering, evaluation, and safe rollout practices, with experience on enterprise AI platforms such as Microsoft Copilot, OpenAI, or Anthropic APIs.
Experience with containerization (Docker/Kubernetes) and operating in regulated or security-conscious environments.
Ability to reason carefully about tradeoffs and long-term maintainability of AI-infused systems, and communicate architecture decisions and technical tradeoffs clearly to non-technical stakeholders.

Compensation: