
Superteams.ai provides fractional AI teams to businesses, acting as an extended R&D unit to build, deploy, and scale bespoke AI solutions. They specialize in sovereign AI solutions for various…

Superteams.ai provides fractional AI teams to businesses, acting as an extended R&D unit to build, deploy, and scale bespoke AI solutions. They specialize in sovereign AI solutions for various…
What they do: Provide on-demand, fractional/full‑stack AI teams to build, deploy, and scale production‑grade generative AI applications
Specialties: Sovereign AI solutions, enterprise AI agents, ClimateTech, EdTech, Healthcare, and an AI writing copilot called Supercraft
Founded: 2022 (legal name: Supercraft Inc.)
Team size (self-reported): About 10 employees; 500+ talent pool claimed
Investors/supporters: Point One Capital; angel investors listed on company site
Bridging enterprise demand for productionized generative AI and limited internal AI engineering capacity, with emphasis on data privacy and sovereign deployment.
2022
Technology, Information and Internet
Point One Capital listed as a supporter/lead investor on public company pages; company site also lists several angel investors and startup program supporters
“Supported by Point One Capital and several angel investors listed on the company site”
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Superteams.ai helps businesses build agentic systems, deploy private LLMs, and power next-gen AI workflows. Our company blends AI expertise, cloud infrastructure, and open-source technologies to help clients build, scale, and maintain custom AI solutions across sectors like education, climate, and enterprise SaaS.
Our work spans a wide spectrum of Generative AI applications - from LLMs and vision models to audio synthesis and predictive analytics. If you’re passionate about infrastructure that supports cutting-edge AI systems, you’ll thrive here.
What You’ll Do
As a MLOps Engineer
, you will play a critical role in deploying, managing, and scaling infrastructure that powers AI systems. You’ll work closely with AI developers and product teams to automate deployment, monitor performance, and ensure uptime and reliability across various environments.
Key Responsibilities
Set up and manage cloud infrastructure (AWS, GCP, or Azure) for AI and data applications.
Must-Have Skills
Nice to Have
Experience with vLLM for LLM serving and handling batching, queueing, retries and error handling with LLM requests.
Working knowledge of Python
for scripting and automation. You should be able to understand Python code, debug it to some extent and fix issues that may happen in production.
What You’ll Gain
If you're excited to build scalable infrastructure that enables cutting-edge AI, we’d love to hear from you.
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Build and maintain CI/CD pipelines for deploying AI systems and services.
Containerize applications using Docker and orchestrate using Kubernetes.
Set up observability and monitoring tools such as ELK, Prometheus, Grafana, Loki, and Graylog.
Manage logging, alerting, and performance tracking for uptime, latency, and failure detection.
Automate infrastructure provisioning and updates using IaC tools and scripting.
Collaborate with AI engineers to enable smooth deployments of LLMs and agentic systems.
Assist in database performance optimization (SQL, NoSQL and Vector DBs).
Very strong command of Linux/Ubuntu
systems and shell scripting. You should be able to operate a remote server comfortably.
Hands-on experience with at least one cloud platform: AWS, GCP, or Azure
. Just being able to see the dashboard on AWS isn’t enough - you should know how to manage instances, track system health, handle firewalls, and audit logs.
Proven expertise in CI/CD pipeline management
. You should have worked with Jenkins, Ansible or any industrial-grade CI/CD platform.
Solid understanding of Docker
and Kubernetes
. You should have managed containers, Docker swarms, or handled scalability challenges in production systems.
Experience with monitoring, alerting
, and log centralization tools
like Elastic-Kibana, Prometheus, Grafana, Graylog or Loki. You should also be aware of Sentry and other monitoring systems.
Experience managing uptime, load balancing
, and failover systems
. Understanding of snapshotting, firewalls, recovery, failover and zero-downtime is a must.
Deep experience with SQL databases
(e.g., PostgreSQL, MySQL).
Interest in or exposure to AI infrastructure
, model serving, and agentic system design.