Senior AI / Agentic-Infrastructure Engineer: need multi-agent development for projects at GPU scale

Good day! I'm a technical founder running several concurrent, high-complexity workstreams, from production AI systems to a deep-research group. I already work with AI coding agents, but I'm finding that I'm the bottleneck. I need someone far more advanced at multi-agent orchestration to build, or bring and customize, a production-grade "agentic development organization" that I plug my own GitHub, Anthropic/Claude (Claude Code), VS Code, and compute into, so I can run multiple agents and projects in parallel, coherently, and multiply my own output across everything I do. Optionally, you can also co-build alongside to accelerate delivery of certain projects (NDA required). I see this being two phases: Phase 1 — Build (or stand up) & teach me the agentic development organization A production-grade multi-agent setup I plug my own accounts/tools into: many agents in parallel, git worktrees, background/remote agents, agent fleets across multiple machines, orchestration, CI/CD + eval/test automation. Elastic GPU/CPU compute — provision and autoscale heavy compute (cloud based for now) so slow hardware stops being the bottleneck; cost controls built in. A shared memory + knowledge backbone (persistent state, retrieval, knowledge graph) so nothing is lost between sessions and work stays connected. A verification spine, the system's #1 job: many agents across many projects must compose into one coherent whole with a zero-defect standard (verification gates, no silent failures), not a swarm that drifts. Document everything and train me: I want a capability I own and can run solo, reusable across all my projects. No black boxes, no consultant-dependency. Phase 2 (optional): Co-building. Pair on non-core layers: installers/cross-platform packaging, dashboards, CI/devops, IDE integration, eval/benchmark harnesses, self-host deployment/hardening. All proprietary/IP details shared only after NDA + IP-assignment are signed. IP core stays in-house. Required skills: Multi-agent orchestration / agentic development — proven, hands-on. You've designed and operated systems where many AI agents work in parallel. Comfortable with Claude Code / agent SDKs, MCP, agent evals/guardrails. Compute & MLOps at scale: GPU/CPU orchestration + autoscaling (Kubernetes, Ray, Slurm, cloud GPU: AWS/CoreWeave/Runpod/Lambda), cost management. DevEx / automation — Git at scale (worktrees, branching), CI/CD, reproducible environments. Strong polyglot backend/systems, primarily Python (FastAPI); comfort with Go, TypeScript/Node, ideally C++/CUDA. Cloud + infra: AWS (ECS/Fargate, Lambda, ALB/CloudFront), Terraform/IaC, Postgres (+pgvector), Redis, containers, SSE. Memory infra: vector DB + graph DB or similar. Reliability & verification discipline: you can explain how you keep parallel agents coherent and correct, not just fast. Zero-gaps/zero-shortcuts is a design requirement. Required experience: - 5+ years professional engineering, including production AI/LLM infrastructure. - Demonstrated agentic/multi-agent orgs or pipelines: concrete, show-me examples (repos, demos, write-ups, talks). What you built vs. off-the-shelf. - Shipped ≥1 production, enterprise-grade system (security, reliability, deployment). - Bonus: GPU/CUDA or memory/performance work, LLM gateways/inference optimization, ML-research infra. - Track record of documenting and transferring complex setups (no dependency traps). Technology & access you must have: - Your own powerful hardware and/or cloud: ideally multiple machines; capable of heavy parallel agent + GPU workloads. - Your own Claude Code / agent tooling and model accounts for testing (BYO-key, incl. OpenRouter). - GPU access (cloud or local) for the performance portions, or a clear plan to provision it. - Confidentiality & IP (non-negotiable) NDA + full IP-assignment signed before any access to code, accounts, or product details (my counsel's templates; cross-border enforceability matters). - All work product and IP are mine; no reuse of any code/methods/concepts elsewhere. - Scoped, revocable access only; secure credential practices (no raw passwords; scoped tokens / supervised pairing); identity verification + references for anyone near the core. Engagement: Open to a custom build or customizing a platform you already own. Starts with a small paid trial task (stand up the Phase-1 environment), then milestone-based, with potential ongoing/long-term work. Budget is a placeholder and negotiable. How to apply (read carefully — proposals that skip this are ignored): 1. Show a real agentic/multi-agent system you built: repo, demo, write-up, or talk. What you built vs. used. 2. In 3–5 sentences: a multi-agent pipeline you ran in production, and one hard orchestration/coherence problem you solved. 3. Your hardware/compute + GPU access. 4. How you'd guarantee coherence and correctness across many parallel agents/projects, briefly. 5. Confirm you'll sign NDA + IP-assignment and start with a paid trial. Start your proposal with the word "AGENTIC" so I know you read this. Thank you for your time and reply. Looking forward to discussing more and working together!