AI-native Technical Lead

Unimatch Lab is an AI-driven Venture Studio based in Silicon Valley.

We are building our own AI technology stack and a portfolio of AI-driven assets: from consumer AI products and smart devices to local LLM clusters and foundational layers (memory layer, RAM/VRAM optimization, orchestration, AI software for infrastructure and compute). This includes R&D in local, distributed, and orbital data centers and distributed computing.

Goal: become a top-50 AI company globally with a combined asset valuation of $10B by 2032.

We are an OKR-driven company: we prioritize measurable results, speed, transparency, and ownership. We hire A-players: autonomous, fast, with strong execution and a high sense of accountability.

Who we're looking for

A Tech Lead at Unimatch is not a traditional tech lead who writes code and mentors juniors. This is an engineering system orchestrator: someone who designs development processes so that routine work is handled by AI agents, while engineers focus on architecture and quality.

You think in systems, not tasks. In every area — from CI/CD to code review, from tech debt control to engineering analytics — you design automation: which agents operate, under what rules, with what metrics and feedback loops. Where others hire people, you build a system.

The Tech Lead influences through technical expertise, systems thinking, and automation — not through people management.

Candidate profile

You are an engineer with a strong production background who grew from hands-on development into systems thinking. For you, it's natural not just to solve a problem, but to build a process where problems are solved automatically.

• You design engineering processes as a system: standards, automation, metrics, feedback loops
• You see routine and immediately think about how to automate it with an agent, not with manual effort. You build a team only when necessary, based on this principle
• You make architectural decisions autonomously and own the consequences
• You build knowledge bases and standards so the team operates by a system, not by verbal agreements
• You iteratively evolve automation: task coverage, agent quality monitoring

Must have

• 7 years in software development with a strong production background — before and after the AI era. Backend, frontend, DevOps — architecture of scalable systems
• 3 years of technical leadership (IC track): architectural ownership, standards, review culture, technical interviews
• Software architecture: system design, patterns, trade-off analysis, ADR
• AI/agent orchestration in engineering workflows: hands-on experience designing and deploying agents for CI/CD, code review, quality monitoring, engineering analytics. Not "I know what LangChain is" but "I built a system where agents handle specific engineering tasks"
• CI/CD & DevOps: pipelines, deployment automation, monitoring, rollback — and experience automating these with agents
• Tech debt management: inventory, prioritization, elimination strategy — as a systematic process, not a one-off initiative
• Observability & evaluation: OpenTelemetry, Langfuse, Prometheus, Datadog (or equivalents) — for monitoring both services and agents
• Proven track record of reliable web/mobile products with production releases
• Incident management: diagnostics, resolution, post-mortems, prevention
• English B2 (working proficiency)

Nice to have

• Python, FastAPI
• Startup, venture studio, or multi-product experience
• LLM tools: LangChain, LangGraph, Mastra, CrewAI, Autogen, HuggingFace, OpenAI, Claude, Mistral
• LoRA, QLoRA, PEFT — inference and fine-tuning
• Model Context Protocol (MCP), function calling, structured outputs
• Deep understanding of LLM infrastructure: RAG, embeddings, vector DBs; Voice AI, Computer Vision, multimodal
• Experience building evaluation frameworks for agents: reliability, safety, performance

What we offer

• Total compensation starting at $8,000/month — no ceiling, depends on your speed, performance, and contribution
• Options / product equity — earn equity in the products you develop and lead
• Full freedom — remote, flexible schedule, complete autonomy
• Make key technical decisions, influence architecture, stack, and processes
• Launch your own startup within the Venture Studio — with our infrastructure, team, funding, and network
• Work with top Silicon Valley venture funds and strong, professional teammates
• AI product exposure — our goal is to ship a portfolio of AI products. Every month you see, test, and ship the best AI solutions in production

You can apply here or write on telegram with your CV @unimatch_work