Tech Lead (AI + Full Stack/ Python) - Hands-On Builder

About InVitro Capital:
InVitro Capital is a U.S.-based venture studio and fund. We build and fund companies from idea to exit, focusing on technology-driven businesses that solve real-world problems. Our portfolio spans healthcare, home services, and sales technology.
Our engineering philosophy is simple: small senior teams, extreme ownership, hands-on builders, and AI-native products. We do not bolt AI onto products — we design AI-native systems from day one.
We operate with a builder culture where engineers have end-to-end responsibility for launching and scaling AI-powered products across the studio.

Role Overview:
We are looking for an exceptionally strong Tech Lead (AI + Full Stack) who codes every day and leads through architecture, execution, and example. This role is designed for elite senior builders who thrive in zero-to-one environments, enjoy solving complex problems, and can ship production-grade systems quickly.
This is a full-stack tech lead role first: you will architect and ship end-to-end product systems (backend + frontend collaboration), and you must also be strong enough in AI/ML to build and productionize AI capabilities inside those systems.

You will:

• Architect core systems
• Build them with your own hands
• Integrate AI tooling & agents
• Mentor engineers through technical leadership
• Drive engineering excellence across multiple ventures

This is not a people-management role — it is a high-impact IC leadership role.

What You’ll Do:
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:
Qualifications:
Required::

• 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:
What We Offer:

• Compensation: $4,000–$5,000 USD/month base + bonus
• 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

Schedule & Work Setup:

• Cairo-based candidates preferred
• Hybrid: expected at the Cairo office at least once per week
• Monday–Friday, aligned with U.S. Pacific Time
• High-autonomy, high-velocity engineering environment