Lead FullStack Engineer

Capital Placement; Abu Dhabi; On-site; AED 320,000 - 700,000; Full time

Job summary

Capital Placement is seeking a seasoned Lead Full Stack Engineer to own the technical direction of our product engineering team in Abu Dhabi. You will architect backend systems in Node.js, deliver frontend features with React/Next.js, and integrate AI capabilities into data pipelines and automation.

The role requires building scalable architectures, mentoring engineers, and driving AI‑first development practices to improve velocity and product quality.

Qualifications

• 6–10 years of experience in full‑stack or AI/ML product engineering.
• Proven backend and frontend delivery across REST/GraphQL APIs and UI using React/Next.js.
• Experience leading cross‑functional teams and shaping technical direction.
• Hands‑on with Node.js, Python, and cloud services (AWS/GCP/Azure).
• Familiar with AI integration, LLMs, data pipelines, and DevOps practices.

Responsibilities

• Own the technical roadmap and architecture across backend, frontend, and AI components.
• Lead a cross‑functional team of backend, frontend, and AI engineers; mentor others.
• Design scalable microservices, data pipelines, and AI‑powered features.
• Ensure code quality, reviews, performance, and observability in production.
• Collaborate with product managers to translate requirements into engineering plans.

Skills

Node.js

TypeScript

React/Next.js

Python

REST API

GraphQL

AWS/GCP/Azure

CI/CD

Docker

Kubernetes

Tools

GitHub Actions

Terraform

Datadog/Grafana

Job description

Lead FullStack EngineerTeam Scope: Backend · Frontend · AI/ML · DevOpsExperience Level: 6–10 YearsKey Stack : Node.js (primary) · Python · TypeScript · React/Next.jsLFFeatured Job# Lead FullStack EngineerTeam Scope: Backend · Frontend · AI/ML · DevOpsExperience Level: 6–10 YearsKey Stack : Node.js (primary) · Python · TypeScript · React/Next.jsFull-TimeAbu Dhabi , UAEOn Site## Job OverviewTeam Scope: Backend · Frontend · AI/ML · DevOpsExperience Level: 6–10 YearsKey Stack : Node.js (primary) · Python · TypeScript · React/Next.js**About the Role**We are looking for a seasoned AI Full Stack Tech Lead to own the technical direction of our product engineering team. Inspired by profiles like senior engineers with a track record across backend services, frontend delivery, and AI product integration — this role demands both depth and breadth. You will architect and build backend systems in Node.js, ship full-stack features using React/Next.js, integrate AI capabilities (LLMs, automation, data pipelines), and lead a cross-functional team of backend, frontend, and AI engineers. You bring a strong AI-first mindset and actively leverage AI coding tools to elevate team velocity.**What makes this role unique*** You are not just a backend engineer — you lead end-to-end: API, UI, and AI* AI is core to the product, not a side feature — LLM integration is day-one work* You actively use AI coding assistants (Copilot, Cursor, Claude Code) and champion them across the team* You will shape architecture decisions that directly affect product performance and customer experience**Key Responsibilities****Backend Architecture & Engineering**• Design and own scalable backend systems using Node.js — REST APIs, microservices, event-driven architecture• Build Python-based services for data pipelines, ML integration, and automation workflows • Architect database schemas and storage strategies across SQL (PostgreSQL) and NoSQL (MongoDB, Redis)• Own observability: structured logging, monitoring, alerting, and performance profiling in production• Drive CI/CD pipelines, infrastructure-as-code, and DevOps best practices across the team Full Stack Development• Build and review frontend features using React / Next.js and TypeScript• Define frontend architecture standards: component design, state management, API integration patterns• Collaborate with designers and product managers to deliver polished, performant user-facing features• Ensure frontend quality through code reviews, performance audits, and cross-browser compatibility**AI & ML Integration**• Integrate LLM APIs (OpenAI, Anthropic, open-source models) into product features• Design and implement RAG pipelines, prompt engineering workflows, and AI-powered automation• Work with the AI research team on model serving, embedding pipelines, and vector search (e.g. pgvector, Pinecone)• Own reliability and cost tradeoffs for AI features in production — latency, token budgets, fallback strategies**Team Leadership*** Lead a cross-functional team of backend, frontend, and AI engineers — day-to-day technical direction* Conduct regular code reviews, architectural reviews, and technical design sessions* Mentor engineers at all levels; define team engineering standards and growth paths* Own the technical roadmap and translate product requirements into clear engineering plans* Champion AI coding tools across the team — establish best practices for AI-assisted development* **Required Skills & Experience**● Node.js — 6+ years, expert level● TypeScript — strong, production experience● REST API & GraphQL design● PostgreSQL / MySQL — schema design & tuning● AWS / GCP / Azure — cloud-native services● CI/CD — GitHub Actions, pipelines, IaC● AI coding tools — Copilot, Cursor, or similar● System design & architectural decision-making● Agile / iterative product delivery● Cross-functional team leadership (5+ engineers)● LLM API integration (OpenAI / Anthropic)● Docker & Kubernetes● MongoDB / Redis / caching strategies● Microservices & distributed systems● React / Next.js — full stack delivery● Python — proficient (FastAPI, Django, scripts)**Nice to Have*** AI/ML frameworks: LangChain, LlamaIndex, Hugging Face, open-source LLMs (Mistral, LLaMA)* Vector databases: Pinecone, Weaviate, Qdrant, or pgvector for RAG pipelines • Data engineering: ETL pipelines, data streaming (Kafka), or time-series systems • DevOps depth: Terraform, Helm, advanced Kubernetes, or observability platforms (Datadog, Grafana)* Product sense: Experience working on AI-native or automation-first products* Open source: Active contributions to open source projects or a visible technical portfolio