Job Description
Job Description
Mission
4Minds is an enterprise AI fine-tuning platform that transforms how organizations build and operate private, domain-specific AI. Unlike static systems, 4Minds’s AI platform learns continuously from live data in real time and can be deployed on-prem or your cloud provider.
Our patented technologies scale existing engineering teams and empower new AI teams, enabling rapid AI deployment, adaptation, and ROI. Through 4Minds’s automated data pipeline and proprietary knowledge graph, enterprises can connect all their data sources, including Microsoft, Databricks, AWS and Google, creating adaptive AI that surpasses the capabilities of conventional RAG-based systems.
Role Overview
We're seeking a DevOps Engineer to build and maintain the infrastructure that powers our enterprise AI platform across cloud and on-premises environments. You'll design scalable deployment pipelines, ensure system reliability, and enable our engineering teams to ship faster while maintaining enterprise-grade security and compliance standards.
You'll take on the infrastructure lifecycle from provisioning through monitoring for our frontend and backend of our platform and support our AI teams to optimize how we build, deploy, and run AI workloads at scale. Our hybrid deployment model, supporting both cloud and on-prem installations, creates unique challenges that require creative solutions.
Reporting to our CTO, you'll have significant autonomy to collaborate on and establish DevOps practices, select tooling, and shape how 4Minds delivers reliable, secure AI infrastructure to enterprise customers.
Key Responsibilities
- Design, implement, and maintain CI / CD pipelines for automated building, testing, and deployment of AI platform components
- Manage infrastructure-as-code across AWS, GCP, Azure, and on-premises environments using Terraform, Pulumi, or similar tools
- Build and maintain Kubernetes clusters optimized for AI / ML workloads, including GPU scheduling and resource management
- Implement monitoring, logging, and alerting systems to ensure platform reliability and rapid incident response
- Develop and enforce security best practices, including secrets management, access controls, and compliance automation
- Collaborate with engineering teams to containerize applications and optimize deployment workflows
- Create and maintain documentation for infrastructure, deployment procedures, and runbooks
- Automate operational tasks to reduce toil and improve team velocity
- Support enterprise customer deployments, including on-premises installations with unique infrastructure requirements
- Optimize infrastructure costs while maintaining performance and reliability standards
Required Qualifications
BS in Computer Science, Engineering, or related technical field5+ years of experience in DevOps, SRE, or infrastructure engineering rolesStrong proficiency with cloud platforms (AWS, GCP, or Azure), including compute, networking, and security servicesHands-on experience with Kubernetes in production environments, including deployment, scaling, and troubleshootingExpertise with infrastructure-as-code tools (Terraform, Pulumi, CloudFormation, or similar)Experience building and maintaining CI / CD pipelines (GitHub Actions, GitLab CI, Jenkins, or similar)Strong scripting skills in Python, Bash, or Go for automationSolid understanding of networking fundamentals, including DNS, load balancing, and firewallsExperience with monitoring and observability tools (Prometheus, Grafana, Datadog, or similar)Ability to work autonomously and drive technical decisions in a fast-paced environmentClear technical communication with both technical and non-technical stakeholdersDeep ownership mindset : you care about outcomes, not job titlesPreferred Qualifications
MS in Computer Science, Engineering, or related technical field7+ years of experience in DevOps, SRE, or infrastructure engineering rolesExperience supporting AI / ML infrastructure, including GPU clusters and model servingBackground with on-premises or hybrid cloud deployments for enterprise customersExperience with data pipeline infrastructure (Kafka, Airflow, or similar)Familiarity with security compliance frameworks (SOC 2, HIPAA, FedRAMP)Track record of establishing DevOps practices and culture on engineering teamsExperience with service mesh technologies (Istio, Linkerd)Contributions to open-source infrastructure projectsPrevious enterprise software or B2B SaaS experienceCompensation
Base salary range : $140,000 - $160,000 annuallyCompetitive equity package in venture-backed startupPerformance-based bonus structureAnnual merit-based salary reviewsStockBenefits
Comprehensive medical, dental, and vision coverage (80% employer-paid)401(k) plan with company matchUnlimited PTO policy with 15 days minimum11 paid company holidaysFlexible Spending Account (FSA) and Health Savings Account (HSA) options.Professional Development
Annual training and certification budgetAccess to online learning platformsConference attendance opportunitiesRegular internal technical workshops and knowledge sharing sessionsWork Environment
Onsite in Dallas 5 days a week.High-performance workstationsModern office space in Dallas with standing desks and ergonomics equipmentMonthly team events and learning sessionsCollaborative in-office environment fostering innovation and teamworkProcess
We like to be efficient but do our due diligence. Here’s what you’ll expect from us :
Interview with Recruiter (30-60 minutes)Interview with Hiring Manager (30 minutes)Technical Interviews and Presentation (Half Day)Interview with CEO (45 Minutes)Apply Now :
Hit the apply button and submit :
Detailed ResumeGit Hub profile or code samplesPortfolio of relevant workBrief cover letter describing your development experienceReferences from previous roles4MindsAI is an equal opportunity employer. We value diversity and are committed to create an inclusive environment for all employees.