A fast-moving engineering organization in Dubai is building production AI agents that change how the company ships code and how employees work with internal knowledge. As an AI Agent Engineer, you’ll join a small, high-ownership team to write the agent logic, the tools, the data layer, and the pipelines that make AI agents dependable at scale — turning architecture into reliable, well-tested, production-grade systems
About the Opportunity – Production AI Agent Engineering
Core Focus: Production-grade LLM agents, RAG pipelines, and AI-powered code tooling
Technical Scope: Agent logic, orchestration, tool use, evaluation harnesses, and observability
Data Layer: Postgres schema design, query optimization, and pgvector indexing
Team Structure: Small, high-ownership team with flat hierarchy and direct impact
Tooling: Git, CI/CD, internal services, and Claude Code-driven development workflows
Global Impact & Innovation Opportunity
Strategic Location: Dubai – a growing hub for AI-native engineering teams in the region
Innovation Focus: Build the AI Code Pipeline’s test-generation and test-execution engine
High Ownership: Own the reliability, latency, and cost of every system you ship
Career Growth: Direct impact in a dynamic international company with a flat hierarchical structure
Position Overview
This AI Agent Engineer role involves implementing agent logic, tools, and orchestration against a given architecture, then turning that architecture into reliable, well-tested, production-grade systems. You will build and tune RAG pipelines end-to-end — ingestion, embeddings, retrieval, re-ranking, and evaluation — design and optimize Postgres schemas and vector indexes for production load, build the test-generation and test-execution engine for the AI Code Pipeline, and integrate with Git, CI/CD, and internal services while owning the reliability, latency, and cost of the systems you ship.
Why This Role Matters: As AI Agent Engineer on a small, high-ownership team, you directly shape how an engineering org ships code and how employees interact with internal knowledge, build RAG pipelines and agent orchestration that operate at real production scale, design Postgres and pgvector data layers that power dependable AI systems, build evaluation harnesses and guardrails that keep agents measurable and safe, and work in a flat hierarchy where your voice matters and your impact is seen.
Key Responsibilities
Agent Logic & Orchestration
- Implement agent logic, tools, and orchestration against the given architecture
- Turn architecture into reliable, well-tested, production-grade systems
- Build evaluation harnesses, observability, and guardrails so agents are measurable and safe
- Own the reliability, latency, and cost of the systems you ship
RAG Pipeline Development
- Build and tune RAG pipelines covering ingestion, embeddings, retrieval, re-ranking, and evaluation
- Optimize retrieval quality and relevance for internal knowledge use cases
- Continuously evaluate and improve pipeline performance at scale
- Apply tool use and function-calling techniques to agentic workflows
Data Layer & Postgres Engineering
- Design and optimize Postgres schemas, queries, and vector indexes for production load
- Work hands-on with pgvector extensions for embedding storage and retrieval
- Ensure data layer performance scales with growing agent and pipeline demands
- Build the test-generation and test-execution engine for the AI Code Pipeline
Integration, Testing & Code Quality
- Integrate with Git, CI/CD, and internal services
- Automate software testing across unit, integration, functional, security, and performance levels
- Write clean, typed, well-tested Python and actively participate in code review
- Integrate AI agent tooling with developer workflows and CI/CD systems
Qualifications & Requirements
Experience Requirements
- 4+ years of professional software engineering experience in Python, with deep, hands-on command of async, typing, packaging, and performance
- 1+ years building LLM or agentic systems — tool use, function calling, orchestration, prompting, and evaluation
- 6+ months of demonstrated experience building with Claude Code in a development workflow
- Experience shipping and operating production services, including testing, CI/CD, and observability with an on-call mindset
Essential Skills
- Strong problem-solving and debugging skills on ambiguous, real-world production problems
- Solid Postgres experience including schema design, query optimization, and extensions such as pgvector
- Comfort with Git-based workflows and active participation in code review
- Experience automating software testing — unit, integration, functional, security, and performance
- Experience integrating with developer tooling and CI/CD systems
- Ability to write clean, typed, well-tested, and maintainable Python code
Company Benefits
- Opportunity to work for a dynamic international company with a flat hierarchical structure
- Direct ownership where your voice matters and your impact is clearly seen
About the Production AI Agent Opportunity
Join a small, high-ownership engineering team building production AI agents that reshape how code gets shipped and how employees access internal knowledge. The role spans agent logic, RAG pipelines, Postgres and pgvector data engineering, and CI/CD integration, all within a flat hierarchical structure where individual contributions are visible and valued — offering strong career growth for engineers who want to build dependable, measurable AI systems at scale.
Career Excellence: Lead production AI agent and RAG pipeline engineering for a dynamic international company with real ownership.
Who Should Apply?
- Senior Python Engineers: With 4+ years of production experience and async/typing expertise
- LLM & Agentic Systems Builders: With hands-on tool-use, orchestration, and prompting experience
- RAG Pipeline Specialists: Skilled in ingestion, embeddings, retrieval, and re-ranking workflows
- Postgres & pgvector Engineers: Comfortable optimizing schemas and vector indexes at scale
- Claude Code Power Users: With 6+ months of demonstrated experience in AI-assisted development workflows
Recently Opening Job👇
