AI Engineer wanted at Abu Dhabi to design, develop, and deploy Generative AI and Agentic AI solutions for enterprise-scale business applications. The role involves building intelligent systems that integrate complex backend services with client-facing applications across web, mobile, and enterprise platforms.
AI Engineer will be responsible for developing AI-powered applications, autonomous agents, and multi-agent workflows while collaborating closely with architecture, engineering, product, and business teams. This role requires strong technical expertise, hands-on development skills, innovative thinking, and a commitment to delivering scalable, secure, and high-quality AI solutions.
Key Responsibilities -AI Engineer
- Design and develop Generative AI applications using Large Language Models (LLMs).
- Build Agentic AI solutions, including autonomous agents, multi-agent systems, and workflow-driven decision engines.
- Develop AI applications using frameworks such as LangChain, LangGraph, and similar agent orchestration frameworks.
- Design and implement Retrieval-Augmented Generation (RAG) architectures using vector databases.
- Work with embeddings, vector databases, semantic search, and AI model evaluation techniques.
- Apply Context Engineering strategies to optimize token usage, response quality, and application latency.
- Implement advanced RAG strategies to improve retrieval speed, accuracy, and answer relevancy.
- AI Engineer Develop effective prompt engineering, tool calling, memory management, and agent orchestration strategies.
- Integrate AI services with enterprise APIs, middleware, backend systems, and third-party platforms.
- Evaluate and continuously improve AI agent performance using appropriate technical and business metrics.
- Design and deploy scalable AI solutions across Microsoft Azure and AWS cloud environments.
- Implement AI model evaluation, guardrails, observability, monitoring, and AI governance practices.
- Architect end-to-end data indexing pipelines optimized for semantic search and RAG applications.
- Design resilient data ingestion pipelines supporting high availability, scalability, and low-latency vectorized datasets.
- Deploy and manage AI workloads using Kubernetes and cloud-native technologies.
- Collaborate with product owners, enterprise architects, software engineers, and business stakeholders to translate business requirements into scalable AI solutions.
- Identify technical debt, architecture improvements, and opportunities for continuous optimization of existing AI and software systems.
Skills – AI Engineer
- Bachelor’s degree in Computer Science, Computer Engineering, Software Engineering, or a related discipline.
- Approximately 10 years of overall professional experience, including at least 3 years of relevant AI Engineering experience.
- Strong experience working in Agile software development environments.
- Hands-on expertise in modern software architecture and engineering practices, including:
- Microservices
- Containers
- Cloud computing
- APIs
- Continuous Delivery
- Event-driven architecture
- Evolutionary architecture
- Strong understanding of software architecture principles, design patterns, quality attributes, and architectural trade-offs.
- Strong programming skills in Python, with experience using technologies such as:
- NumPy
- pandas
- FastAPI
- PyTorch and/or TensorFlow
- Practical experience with LangChain and LangGraph or comparable AI agent frameworks.
- Strong knowledge of LLMs, Generative AI, RAG, embeddings, vector databases, prompt engineering, and agentic AI.
- Experience designing and implementing semantic search and RAG data pipelines.
- Experience with Amazon Bedrock, Azure OpenAI Service, and/or Google Vertex AI.
- Experience integrating AI APIs for Speech-to-Text, Computer Vision, and Natural Language Processing (NLP).
- Experience with serverless technologies such as AWS Lambda and Azure Functions for AI inference and data preprocessing.
- Experience with CI/CD technologies such as Jenkins and GitLab in cloud-native environments.
- Experience developing cloud-based and on-premises application pipelines with static code analysis, requirement tracking, and Jira integration.
- Knowledge of DevOps and configuration management tools.
- Experience deploying and managing AI workloads in Kubernetes environments.
- Experience with monitoring and observability tools across traditional and cloud environments.
- Strong analytical, problem-solving, and systems-thinking abilities.
- Excellent communication and collaboration skills with the ability to work effectively across technical and business teams.
- Demonstrated leadership skills and a proactive, growth-oriented approach to technical problem solving.
Preferred Candidate Profile
The ideal candidate is a hands-on senior technology professional with strong expertise in AI Engineering, Generative AI, Agentic AI, cloud architecture, and enterprise software development. The candidate should be comfortable working across the full AI solution lifecycle—from architecture and data ingestion to model integration, agent orchestration, deployment, monitoring, and continuous improvement.
Strong leadership, communication, collaboration, and stakeholder-management skills are essential, along with a passion for building reliable, scalable, and production-ready AI solutions.
Employment Details
Job Title: AI Engineer
Location: Abu Dhabi, UAE
Employment Type: Full Time
Industry: IT – Software Services
Department: IT Software