Hybrid Tech Lead – AI, Full Stack

Posted 3 hours ago

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About the role

  • Tech Lead (AI + Full Stack) at InVitro Capital building AI-native products with hands-on engineering and leadership.

Responsibilities

  • Architect core systems
  • Build them with your own hands
  • Integrate AI tooling & agents
  • Mentor engineers through technical leadership
  • Drive engineering excellence across multiple ventures
  • Build & Lead With Technical Depth (70–90% hands-on)
  • Architect, build, and ship backend and full-stack systems end to end.
  • Lead engineers through code reviews, architecture reviews, and solid technical decision-making.
  • Own engineering execution across multiple ventures.
  • Design Scalable, AI-Native Architectures
  • Build modular APIs, distributed systems.
  • Embed AI capabilities into product systems (LLMs and/or domain AI like NLP/CV) in a way that is secure, observable, reliable, and scalable.
  • Design and implement retrieval workflows (RAG), evaluation/guardrails, and agent/tool orchestration where they add real product value.
  • Work with Python, OpenAI, Anthropic, LangGraph, LangChain, LlamaIndex, vector databases, and agent toolchains.
  • Engineer With Excellence
  • Write high-performance, production-grade code in Python (primary) for backend services and AI/ML systems.
  • Build and productionize ML/AI components (training/inference pipelines, model serving, and integrations) with strong engineering discipline.
  • Build systems optimized for reliability, performance, and observability.
  • Full-Stack Ownership
  • Collaborate with frontend engineers to deliver seamless end-to-end experiences.
  • Design clean APIs, interfaces, and developer workflows.
  • DevOps + Cloud Execution
  • Manage CI/CD pipelines and cloud deployments on AWS.
  • Kubernetes is a strong plus; AWS + Docker + CI/CD and production deployment ownership are required.
  • Ensure systems are scalable, fault-tolerant, secure, and well-instrumented.
  • Own production deployments of AI/ML components (model serving, monitoring, and lifecycle workflows) alongside the core application stack.
  • Technical Leadership & Mentorship
  • Mentor engineers and uplift technical standards across the stack.
  • Provide architectural direction and guide complex technical initiatives.
  • Contribute to hiring and shaping engineering culture.

Requirements

  • Professional Engineering Experience — 12+ years building and shipping production-grade systems.
  • Python Expertise (FastAPI or similar, production) — async services, Pydantic models, you write Python daily.
  • Backend/System Architecture Ownership — you’ve owned system design decisions, led code reviews, mentored engineers, and shipped end-to-end systems as a senior IC or tech lead.
  • Core ML / Deep Learning (hands-on) — built ML/DL systems using PyTorch or TensorFlow; understand training, evaluation, optimization.
  • Production ML Deployment / MLOps — deployed ML systems to production; owned monitoring, versioning, rollback strategies, lifecycle management.
  • Applied AI Systems Experience — shipped AI-powered features using LLMs and/or applied NLP/CV in real products (not experimentation only).
  • PostgreSQL — schema design, query optimization, migrations.
  • Cloud + Delivery — AWS + Docker + CI/CD; production deployments and operational ownership.
  • REST API Design — clean interfaces serving multiple clients (web, mobile, service-to-service).
  • Startup Execution — experience in fast-paced, high-ownership environments.
  • Strong Plus:
  • Ruby on Rails (production) — built and maintained real Rails APIs with background jobs (e.g., Sidekiq), webhooks, and complex domain logic.
  • Kubernetes (production) — EKS (or equivalent), Kubernetes-based deployments, operational ownership.
  • GenAI Depth — experience designing RAG systems, prompt strategies, fine-tuning workflows, and evaluation/guardrails.
  • Retrieval & Vector Systems — vector databases (Pinecone, Weaviate, or similar), embedding strategies, namespace/tenancy design, reranking.
  • Agent Orchestration — multi-agent patterns, tool use, chain composition (CrewAI, LangGraph, or similar).
  • AI Tooling Ecosystem — LangChain, LlamaIndex, Hugging Face, or similar; LLM observability/tracing (LangSmith or equivalent).
  • Full-Stack Fluency — strong collaboration with frontend teams to ship end-to-end product experiences; clean API contracts.
  • React 19 (JavaScript) — Redux Toolkit, RTK Query, Vite, shadcn/ui.
  • Flutter/Dart — mobile app development, BLoC pattern, Clean Architecture.
  • Firebase/Firestore — real-time sync, Cloud Functions.
  • Stripe — payment processing, webhook-driven architecture, Connect.
  • MongoDB — document modeling; async drivers (Motor) is a plus.
  • Multimodal AI — vision models; real-time audio/video AI (LiveKit, OpenAI Realtime API).
  • Redis + Sidekiq — background job processing, caching.
  • 0→1 / Venture Studio Experience — building products from scratch in multi-product, high-velocity environments.

Benefits

  • Health insurance
  • Social insurance
  • Paid Time Off (PTO)
  • High ownership and autonomy
  • Opportunity to build multiple AI-powered products from scratch
  • A culture optimized for speed, impact, and technical excellence

Job title

Tech Lead – AI, Full Stack

Job type

Experience level

Senior

Salary

$4,000 - $5,000 per month

Degree requirement

Bachelor's Degree

Location requirements

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