Dragos

2 months ago

Manager, AI and Cloud Solutions

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 4 hours agoStatus: Live

Job Summary

Lead the design, deployment, and operation of enterprise cloud infrastructure on AWS and Azure while guiding a small team of cloud and AI engineers. Own AI tooling lifecycle from POC to production, integrate copilots and enterprise apps via APIs, and ensure reliability, security, and cost efficiency across multi-cloud environments.

Location: United States

Workplace: Remote

Employment Type: Full time

Job Function: Data Science & Machine Learning

Seniority: Manager level

Key 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

Pay and Benefits

Salary: USD 165,000 annually

Equity and Bonus:Equity

Perks:Equity

Key Requirements

•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

Experience:3+ yearsCybersecurityAICloud computingSaaS

Skills:LeadershipMentoringCommunicationProblem-solving

Languages:English

Tech Stack:AWSAzureServerlessIAMVPCSavings PlansOpenAIMicrosoft CopilotAnthropicDockerKubernetesAPIsWebhooks

Company Brief

Dragos

Provides industrial cybersecurity solutions protecting operational technology (OT) and industrial control systems (ICS) with threat detection, incident response, and asset visibility to secure critical infrastructure and manufacturing environments.

Industry: Cybersecurity

Company Size: Large (251 to 1,000 employees)

Growth: Scaleup

Valuation: Unicorn (USD 1B+)

Funding: Series D

Headquarters: Washington, D.C., United States

Founded: 2016

Website LinkedIn

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Dragos

2 months ago

Manager, AI and Cloud Solutions

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 4 hours agoStatus: Live

Job Summary

Location: United States

Workplace: Remote

Employment Type: Full time

Job Function: Data Science & Machine Learning

Seniority: Manager level

Key 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

Pay and Benefits

Salary: USD 165,000 annually

Equity and Bonus:Equity

Perks:Equity

Key Requirements

•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

Experience:3+ yearsCybersecurityAICloud computingSaaS

Skills:LeadershipMentoringCommunicationProblem-solving

Languages:English

Tech Stack:AWSAzureServerlessIAMVPCSavings PlansOpenAIMicrosoft CopilotAnthropicDockerKubernetesAPIsWebhooks

Company Brief

Dragos

Industry: Cybersecurity

Company Size: Large (251 to 1,000 employees)

Growth: Scaleup

Valuation: Unicorn (USD 1B+)

Funding: Series D

Headquarters: Washington, D.C., United States

Founded: 2016

Website LinkedIn