Qureos Mentor

Yalent

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 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.
 
You will: 
<ul>
<li>Architect core systems</li>
<li>Build them with your own hands</li>
<li>Integrate AI tooling & agents</li>
<li>Mentor engineers through technical leadership</li>
<li>Drive engineering excellence across multiple ventures</li>
</ul>
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)
 <ul>
<li>Architect, build, and ship backend and full-stack systems end to end.</li>
<li>Lead engineers through code reviews, architecture reviews, and solid technical decision-making.</li>
<li>Own engineering execution across multiple ventures.</li>
</ul>
Design Scalable, AI-Native Architectures
 <ul>
<li>Build modular APIs, distributed systems, and cloud-native microservices (Azure).</li>
<li>Integrate AI models, retrieval workflows, and multi-agent systems into production applications.</li>
<li>Work with Python, OpenAI, LangChain, LlamaIndex, vector databases, and agent toolchains.</li>
</ul>
Engineer With Excellence
 <ul>
<li>Write high-performance, production-grade code (C#/.NET as primary).</li>
<li>Use Python for AI workflows, automation, and data integrations.</li>
<li>Build systems optimized for reliability, performance, and observability.</li>
</ul>
Full-Stack Ownership
 <ul>
<li>Collaborate with frontend engineers to deliver seamless end-to-end experiences.</li>
<li>Design clean APIs, interfaces, and developer workflows.</li>
</ul>
DevOps + Cloud Execution
 <ul>
<li>Manage CI/CD pipelines, IaC, and Kubernetes deployments on Azure.</li>
<li>Ensure systems are scalable, fault-tolerant, secure, and well-instrumented.</li>
</ul>
Technical Leadership & Mentorship
 <ul>
<li>Mentor engineers and uplift technical standards across the stack.</li>
<li>Provide architectural direction and guide complex technical initiatives.</li>
<li>Contribute to hiring and shaping engineering culture.</li>
</ul>
Requirements: 
Qualifications
 Required
 <ul>
<li>12+ years of professional engineering experience, with a deep record of building production systems.</li>
<li>Expert-level proficiency in C#/.NET.</li>
<li>Strong experience designing and scaling cloud-native distributed systems (preferably Azure).</li>
<li>Expertise in microservices, caching, API design, multithreading, and performance optimization.</li>
<li>Real-world experience with AI toolchains, including:</li>
<li>LLMs (OpenAI, Anthropic, etc.)</li>
<li>Agents & tools</li>
<li>Retrieval pipelines & vector databases</li>
<li>LangChain / LlamaIndex or equivalent</li>
<li>Strong SQL and NoSQL experience.</li>
<li>Hands-on experience with Docker, Kubernetes, CI/CD.</li>
<li>Ability to lead technical direction while being highly hands-on (IC-first).</li>
<li>Experience working in fast-paced, high-ownership startup environments.</li>
</ul>
Huge Plus
 <ul>
<li>Python for AI pipelines, data processing, and automation.</li>
<li>Experience in regulated or high-compliance environments.</li>
<li>Experience building 0→1 products, especially in multi-product or venture studio settings.</li>
<li>Experience designing internal platforms or multi-tenant systems.</li>
</ul>
Benefits: 
What We Offer
 <ul>
<li>Compensation: $4,000–$5,000 USD/month base + bonus</li>
<li>Health insurance</li>
<li>Social insurance</li>
<li>Paid Time Off (PTO)</li>
<li>High ownership and autonomy</li>
<li>Opportunity to build multiple AI-powered products from scratch</li>
<li>A culture optimized for speed, impact, and technical excellence</li>
</ul>
Schedule & Work Setup
 <ul>
<li>Cairo-based candidates preferred</li>
<li>Hybrid: expected at the Cairo office at least once per week</li>
<li>Monday–Friday, aligned with U.S. Pacific Time</li>
<li>High-autonomy, high-velocity engineering environment</li>
</ul>

Tech Lead (AI + Full Stack) - 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 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 a highly skilled Senior AI Engineer who thrives at the frontier of applied AI — someone who builds real-world ML and LLM systems, not academic experiments. This role is designed for senior builders who enjoy crafting end-to-end AI pipelines, optimizing models for production, and integrating AI capabilities directly into high-scale products.
 
You will: 
<ul>
<li>Design and train advanced models</li>
<li>Build and optimize data and inference pipelines</li>
<li>Deploy AI systems to production with reliability and scale</li>
<li>Collaborate closely with backend and product teams</li>
<li>Drive excellence across the AI lifecycle</li>
</ul>
This is a hands-on senior IC role for engineers who want to build AI systems that matter.
 
Requirements: 
What You’ll Do
 Build End-to-End AI Systems
 <ul>
<li>Architect and implement data pipelines for training, evaluation, and real-time or streaming inference.</li>
<li>Build, fine-tune, and integrate ML, NLP, LLM, and/or Computer Vision models using Python, PyTorch, TensorFlow, and Hugging Face.</li>
<li>Implement retrieval pipelines, embeddings, and vector database integrations.</li>
</ul>
Deploy Production-Grade AI
 <ul>
<li>Ship reliable, high-performance inference services using Docker, Kubernetes, and cloud platforms (Azure preferred).</li>
<li>Design APIs and microservices that integrate models into user-facing applications.</li>
<li>Optimize inference latency, throughput, and cost efficiency.</li>
</ul>
Model Monitoring & Improvement
 <ul>
<li>Track model drift, accuracy, performance, and stability.</li>
<li>Continuously improve production models through retraining, evaluation, and enhancements.</li>
<li>Implement observability and monitoring across the ML lifecycle.</li>
</ul>
Champion MLOps Excellence
 <ul>
<li>Maintain CI/CD pipelines for ML systems.</li>
<li>Set up and manage experiment tracking, model registries, and reproducibility workflows.</li>
<li>Ensure robust automation and smooth model deployment processes.</li>
</ul>
Qualifications
 Required
 <ul>
<li>10+ years of experience building and deploying ML/AI systems in production.</li>
<li>Advanced proficiency in Python, with strong expertise in PyTorch or TensorFlow.</li>
<li>Strong understanding of machine learning, deep learning, data engineering, and distributed training.</li>
<li>Hands-on experience with LLMs, NLP, CV, or recommender systems.</li>
<li>Strong MLOps and cloud-native engineering experience.</li>
<li>Experience deploying AI systems on Azure, AWS, or GCP.</li>
<li>Proficiency with Docker, Kubernetes, and scalable microservice architectures.</li>
<li>Strong debugging, optimization, and performance tuning abilities.</li>
<li>Experience working in fast-paced, high-ownership startup environments.</li>
<li>Excellent communication and cross-functional collaboration skills.</li>
</ul>
Huge Plus
 <ul>
<li>Experience with streaming inference or real-time ML systems.</li>
<li>Familiarity with monitoring tooling such as Prometheus, Grafana, or ELK/EFK.</li>
<li>Contributions to open-source ML/AI projects or a strong GitHub portfolio.</li>
<li>Experience building 0→1 systems or working in high-growth technical environments.</li>
</ul>
Benefits: 
What We Offer
 <ul>
<li>Compensation: $3,000–$3,800 USD/month base + bonus</li>
<li>Health insurance</li>
<li>Social insurance</li>
<li>Paid Time Off (PTO)</li>
<li>High ownership and autonomy</li>
<li>Opportunity to build advanced AI systems across multiple ventures</li>
<li>A culture optimized for speed, impact, and technical excellence</li>
</ul>
Schedule & Work Setup
 <ul>
<li>Cairo-based candidates preferred</li>
<li>Hybrid: expected at the Cairo office at least once per week</li>
<li>Monday–Friday, aligned with U.S. Pacific Time</li>
<li>High-autonomy, high-velocity engineering environment</li>
</ul>

Senior AI Engineer - Applied AI Builder

Join Yalent and explore 2   exciting career opportunities. They're hiring for various roles with options for remote or on-site work. Apply today and become part of their innovative team.

Yalent

ABOUT_COMPANY

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

Senior AI Engineer - Applied AI Builder