DevOps Engineer
Bespoke Labs
About the job
DevOps Engineer (Freelance | Remote)
Eligible Locations – Global
Type: Freelance – Contract | Remote | 3 Months
About Bespoke Labs
Bespoke Labs is a VC-backed applied AI research startup based in Mountain View, California. We build core infrastructure and reinforcement learning environments that directly train and evaluate intelligent agents—the systems behind AI, not just the tooling around it.
We focus on building the datasets and benchmarks that shape the future of AI. Our work includes OpenThoughts, one of the most widely used reasoning datasets (100K+ monthly downloads, 200+ models trained, 100+ citations), and Terminal Bench, a leading agentic coding benchmark referenced in Claude 4.5 and actively used by frontier AI labs.
About the Role
We’re building a new AI training initiative that requires real-world engineering experience. You’ll help design and document authentic DevOps + backend scenarios based on incidents you’ve handled—outages, scaling issues, secure deployments, distributed systems challenges, and more. Your experience will directly train next-generation AI systems.
What You’ll Do
- Capture real DevOps + backend incidents and convert them into benchmark tasks
- Contribute to secure, scalable, Kubernetes-native architectures
- Work across CI/CD, observability, identity, infrastructure-as-code, and backend services
- Collaborate with our team to build realistic engineering workflows
Required Experience:
We require candidates with 2-12 years of experience and a technical degree, specializing in building secure, scalable platforms. DevOps must have deep expertise in Kubernetes, Terraform, and CI/CD, with a strong preference for secure, offline/isolated deployments. Backend Engineers must be proficient in Go/Python/Java, Docker, gRPC, and Kubernetes-native services, with ML pipeline experience a plus.
All candidates must demonstrate experience across core functional areas and technical tools, choosing at least five each from categories including: Identity & Access Management, Observability, CI/CD Pipelines, and technologies like Keycloak, GitLab CI, Kubernetes, Terraform OSS, and Prometheus + Grafana.
Strong hands-on experience in DevOps and/or Backend Engineering, including:
- Kubernetes, Terraform, CI/CD, k9s, k3s (GitLab CI preferred)
- Go / Python / Java, Docker, gRPC, Kubernetes-native services
- Experience with secure, offline/air-gapped deployments (big plus)
- Familiarity with at least five of the following:
- Identity & Access Management
- Observability (Prometheus + Grafana)
- CI/CD Pipelines
- Keycloak
- GitLab CI
- Terraform OSS
- Kubernetes tools & ecosystem
- ML/Distributed pipelines (nice to have)
What You’ll Find at Bespoke Labs:
- Fully remote, flexible schedule *Perfect for DevOps Engineers seeking high-impact freelance work*
- 3-month contract period
- Prior AI Training experience is NOT mandatory.
Compensation Structure (Output-Based Model)
This role follows a performance-driven output model, you earn based on completed engineering deliverables, not tracked hours.
- $800 – $1000 USD per approved engineering output
- Each deliverable typically requires 10–20 hours of focused engineering work
- Compensation is tied to quality, completeness, and technical complexity
- High-performing contributors commonly complete multiple outputs per week
- Flexible pacing – optimize your workflow, productivity, and earning potential
- Clear acceptance criteria are provided upfront for every deliverable
The model is designed to reward performance and efficiency rather than hours logged, allowing strong contributors to earn significantly more with consistent delivery. (for example, strong contributors can earn significantly more than a typical $30/hr structure, even up to ~$20k/month with consistent delivery)
Bespoke Labs Hiring Process
Shortlisting → Take-Home Test / Interview → Onboarding
Please Note: This is freelance opportunity, we do not offer sponsorships/full time roles. You must be authorized to work in your country of residence.
Apply Now
If you’ve operated systems at scale and want flexible work while shaping next-gen AI, we’d love to hear from you.
To apply for this job please visit www.linkedin.com.