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Senior AI Engineer

2 days ago

Abu Dhabi, Abu Dhabi, United Arab Emirates HNW | Experiences That Work Full time

**Senior AI Engineer (LLMs, Generative AI) | Lead AI Engineer

Job Description:**

We are looking for a Senior AI Engineer specializing in Large Language Models (LLMs) to lead end-to-end AI initiatives from discovery to production. You will own technical direction, collaborate with product and stakeholders, and build scalable LLM solutions (RAG, agents, fine-tuning, evaluation, and deployment). This role blends hands-on engineering with technical leadership and team mentorship.

Responsibilities:

· Lead LLM projects end-to-end: problem framing, solution design, implementation, rollout, and iteration.

· Design and deliver LLM systems: retrieval-augmented generation (RAG), tool or function calling, agent workflows, prompt strategies, and guardrails.

· Build production-ready services (APIs, workers, orchestration) for model inference and LLM applications.

· Own architecture decisions: data flow, vector storage, caching, latency and cost tradeoffs, and reliability.

· Create evaluation strategy: benchmarks, human review loops, regression testing, and monitoring.

· Improve safety and quality: hallucination reduction, grounding and citations, policy filters, and PII handling.

· Mentor engineers, set coding standards, review PRs, and raise overall team execution.

· Communicate clearly with stakeholders: timelines, risks, tradeoffs, and measurable outcomes.

Required Qualifications (5+ years):

·5+ years of experience in software engineering, ML engineering, or applied AI with proven production delivery.

· Strong Python skills and experience building backend services (FastAPI or Flask, async jobs, queues).

· Solid understanding of LLM concepts: token limits, context windows, prompting patterns, tool calling, retrieval and prompt engineering.

· Hands-on experience with at least one of: RAG (vector databases), fine-tuning, or agents and orchestration (LangGraph, LangChain, LlamaIndex).

· Experience with MLOps fundamentals: CI or CD, monitoring, logging, versioning, and reproducibility.

· Strong system design skills covering latency, cost, scaling, and security.

· Ability to lead projects, drive execution, and coordinate across teams.

2 / 2.

Preferred Qualifications:

· Experience delivering production systems on OpenAI / Azure OpenAI (embeddings + chat/function calling), with strong practices around reliability, prompt/version control, evaluation, monitoring, and spend governance.

· Experience with LLM evaluation and QA processes.

· Experience with cloud platforms (AWS, Azure, or GCP), Docker, and Kubernetes.

· Experience building multilingual solutions (Arabic and English) when relevant.

· Experience building advisory/consultant-style AI assistants for enterprise or government use cases, including guardrails, grounding, and human-in-the-loop workflows.

Tech Stack:

· Python, FastAPI, OpenAI API, database for chat history/metadata (PostgreSQL), and a vector store for retrieval (pgvector or managed vector DB)

· Vector storage: pgvector, Pinecone, Weaviate, Chroma, or FAISS

· Orchestration: LangChain, LangGraph, LlamaIndex, or custom workflows

· Observability: LLM tracing (Langfuse/LangSmith) plus application monitoring/logging (OpenTelemetry, centralized logs, dashboards).

· Deployment: Docker, Kubernetes, Terraform

· LLM providers: OpenAI or Azure OpenAI.

Additional Skills (Nice to Have):

· Familiarity with React (Vite-based projects), with the ability to collaborate effectively with frontend teams and understand UI-driven AI requirements.

· Experience integrating AI services into full-stack applications, coordinating between frontend, backend, and AI layers.

· Understanding of how AI outputs are consumed in user interfaces, including usability, clarity, and interaction flows.

· Experience working in cross-functional product teams, translating business and user needs into AI-driven solutions.