Fractional MLOps · LLMOps · Platform Engineering
Senior platform engineering, on a retainer
Self-hosted model serving, inference optimization, Kubernetes ML platforms, GitOps, and on-call reliability — the hard parts of running AI in production, handled by a team that operates this stack every day. No full-time hire required.
Month-to-month · Start in days · Run by operators, not slide-makers
Who it's for
Funded AI startups that need senior platform muscle but aren't ready to hire a full-time staff/principal engineer.
Teams shipping LLM features who keep getting surprised by inference cost, latency, or reliability in production.
Companies with data-residency or privacy requirements that want self-hosted AI done right, not bolted on.
Engineering leaders who need a second set of senior hands on the platform — without a 3-month hiring cycle.
What's included
Self-hosted model serving
Open-weight LLMs (Qwen, Nemotron, and peers) served on your own or owned GPUs — so your data and your costs stay under your control, not a per-token meter.
Inference optimization
Latency, throughput, and cost tuning for production inference — quantization, batching, KV-cache, GPU placement — measured, not guessed.
RAG & vector infrastructure
Retrieval pipelines, embeddings, and vector stores that actually hold up under real query load and stay permissions-aware.
Kubernetes ML platforms
Production-grade clusters, service mesh, and the platform plumbing (autoscaling, scheduling, multi-cluster) that ML workloads need to run reliably.
GitOps & CI/CD
Declarative, signed, reproducible delivery — ArgoCD, image signing, and pipelines that make deploys boring and rollbacks instant.
Observability & on-call
Metrics, tracing, SLOs, and synthetic canaries — so you find out before your users do. We notice, page, and fix.
Retainer tiers
Predictable monthly engagement. Defined projects are scoped on top.
Advisory
A senior platform/LLMOps partner on call.
- Architecture & roadmap review
- Async access + a standing weekly working session
- Inference-cost & reliability audits
- Hands-on for the high-leverage problems
- Month-to-month, cancel anytime
Anchor Retainer
Embedded fractional platform engineering.
- Everything in Advisory, plus:
- Reserved senior engineering capacity each week
- Build & operate: serving, RAG, platform, GitOps
- Observability, SLOs, and on-call reliability
- Signed-supply-chain & security hardening
- Direct Slack channel + priority response
We run the infrastructure we sell
Self-hosted open-weight LLMs on owned GPUs. Multi-cluster Kubernetes with a service mesh. A cryptographically signed supply chain. A voice-AI platform that has run in continuous production for over 200 days, watched by synthetic canaries around the clock. The patterns we bring to your platform are the ones we depend on for ours.
See the proof200+ days
continuous production
Self-hosted
open-weight LLMs, owned GPUs
Signed
supply chain, end to end
24/7
synthetic canaries + SLOs
Questions
What makes this different from a generic MLOps consultant?+
We operate this exact stack in production ourselves — self-hosted open-weight LLMs on owned GPUs, multi-cluster Kubernetes with a service mesh, a signed supply chain, and a voice-AI platform that has run continuously for over 200 days. You're hiring operators, not slide-makers. See the proof page for what that means.
How fast can you start?+
Days, not a hiring cycle. A fractional retainer skips the recruit-interview-onboard months — we scope the first high-leverage problem on the fit call and start there.
Do you work on our infrastructure or yours?+
Yours. We bring the patterns and the operating discipline; the platform stays in your accounts, your clusters, your control. Where it helps, we can run reference workloads on our own infrastructure to de-risk an approach before it touches yours.
Is there a long-term contract?+
No. Both tiers are month-to-month. The retainer is reserved capacity, not a lock-in — if we're not earning it, you stop.
What if we need more than the retainer covers?+
Defined project work (a migration, a platform build-out) is scoped and priced separately on top of the retainer, so the monthly stays predictable and the big pieces stay transparent.
Put a senior platform team on your roster
Book a 30-minute scoping call. We'll find the highest-leverage problem on your platform and tell you, honestly, whether a retainer is the right way to fix it.