Job Description

Job Role:

AI Engineer- UAE Based

Job Summary:

We are seeking a versatile AI Engineer to design, develop, and deploy AI-powered solutions

across various business domains. This role requires a broad understanding of AI/ML

technologies and the ability to translate business requirements into practical AI applications.

Key Responsibilities

AI Solution Development

Design and implement end-to-end AI applications from concept to production Integrate Large Language Models (LLMs) and foundation models into business applications Build RAG (Retrieval-Augmented Generation) systems and conversational AI interfaces Develop autonomous AI agents and multi-agent systems for complex task automation Implement MCP-compliant tool integrations for enhanced agent capabilities Design agent-to-agent communication systems for collaborative problem solving Create distributed agent networks with proper message passing and state synchronization Design and implement AI workflows and orchestration pipelines for business processes Create agentic systems with tool-calling, reasoning, and decision-making capabilities Create proof-of-concepts and MVPs for AI-driven features Develop computer vision, NLP, and predictive analytics solutions based on requirements

Technical Implementation

Write production-quality code in Python and relevant frameworks Implement APIs and microservices for AI model serving Build robust AI agents with error handling, retry logic, and fallback mechanisms Design stateful workflows and agent coordination systems Implement MCP (Model Context Protocol) for standardized tool integration Build agent-to-agent communication systems for collaborative AI workflows Develop protocol adapters for cross-platform agent interoperability Implement tool integrations for agents (APIs, databases, external services) Optimize model inference for latency and throughput requirements Build data pipelines for model training and inference Ensure scalability, reliability, and maintainability of AI systems

Model Management

Fine-tune and adapt pre-trained models for specific use cases Implement prompt engineering strategies for LLM applications Deploy models using cloud services (AWS, GCP, Azure) and edge devices Monitor model performance and implement retraining pipelines Manage model versioning and A/B testing frameworks

Cross-functional Collaboration

Work with product teams to identify AI opportunities and requirements Collaborate with data engineers on data infrastructure needs Partner with DevOps for CI/CD pipeline implementation Communicate technical concepts to non-technical stakeholders Document AI solutions and create technical specifications

Required Qualifications

Education & Experience

Bachelor's degree in Computer Science, Engineering, Mathematics, or related field 3-5 years of experience in AI/ML engineering or related roles Proven track record of deploying AI solutions in production environments

Technical Skills

Core Programming & Frameworks

Strong proficiency in Python and its AI/ML ecosystem (NumPy, Pandas, Scikit-learn) Experience with deep learning frameworks (PyTorch, TensorFlow, or JAX) Familiarity with LLM frameworks (LangChain, LlamaIndex, Semantic Kernel) Experience with AI agent frameworks (Langraph, AgentOps, Temporal) Knowledge of MCP (Model Context Protocol) for tool and context management Understanding of agent-to-agent communication standards and protocols Experience with protocol bridges and agent interoperability solutions Knowledge of workflow orchestration tools (Prefect, Dagster, Apache Airflow for AI pipelines) Understanding of function calling, tool use, and agent-environment interactions Knowledge of web frameworks (FastAPI, Flask, or Django)

AI/ML Expertise

Understanding of machine learning algorithms and their applications Experience with transformer models and attention mechanisms Knowledge of AI agent architectures (ReAct, Chain-of-Thought, Tree-of-Thoughts) Experience building autonomous agents and multi-agent orchestration systems Familiarity with workflow automation tools and agentic frameworks (AutoGPT, CrewAI, AutoGen) Understanding of agent communication protocols (MCP - Model Context Protocol, Agent-to-Agent protocols) Experience implementing inter-agent communication and coordination mechanisms Understanding of task planning, decomposition, and agent memory systems Knowledge of computer vision techniques and frameworks (OpenCV, YOLO) Familiarity with NLP techniques and libraries (spaCy, NLTK, Hugging Face) Understanding of vector databases and embedding techniques

Infrastructure & Deployment

Experience with containerization (Docker) and orchestration (Kubernetes) Knowledge of ML deployment platforms (MLflow, Kubeflow, or SageMaker) Familiarity with cloud AI services (OpenAI API, AWS Bedrock, Google Vertex AI) Understanding of API design and RESTful services Experience with version control (Git) and CI/CD pipelines

Data & Databases

SQL proficiency and experience with relational databases Knowledge of NoSQL databases (MongoDB, Redis) Experience with vector databases (Pinecone, Weaviate, or Chroma) Understanding of data processing and ETL pipelines

Preferred Qualifications

Advanced Skills

Master's degree in relevant field Experience with MLOps practices and tools Deep expertise in building production-grade AI agent systems Hands-on experience with MCP implementation and custom MCP server development Knowledge of agent-to-agent protocol design and implementation Experience building federated agent networks and swarm intelligence systems Expertise in cross-platform agent communication and handoff mechanisms Experience with agent evaluation and testing frameworks Knowledge of agent safety, alignment, and guardrails implementation Experience with complex workflow orchestration and state management Knowledge of distributed computing (Spark, Ray) Familiarity with edge AI deployment Experience with multimodal AI systems Understanding of AI safety and responsible AI practices

Domain Experience

Experience in specific verticals (healthcare, finance, e-commerce, etc.) Knowledge of regulatory requirements for AI systems Experience with real-time AI applications Background in data privacy and security

Soft Skills

Strong problem-solving and analytical thinking abilities Excellent communication skills for technical and non-technical audiences Self-motivated with ability to work independently Curiosity and passion for staying current with AI advancements Experience mentoring junior team members

Why Join Us:

Cutting-Edge Work: Be part of a company that is redefining mobility tech through innovative solutions. Collaborative Culture: Work alongside passionate engineers, product thinkers, and designers in a fast-paced environment. Growth Opportunities: Get exposed to global projects, leadership responsibilities, and upskilling platforms. Impact at Scale: Build technology that reaches thousands of users across the MENA region and beyond. Employee-Centric Benefits: Competitive salary, visa support, and the opportunity to grow your career in a thriving tech ecosystem.
If you're driven to create impactful mobile experiences and thrive in a fast-evolving tech environment, apply now and drive the future of mobility with us, - we want to hear from you!

Apply Now - Send your CV to talent@self-drive.ae

Workplace Type:

Onsite

Application Open:

Apply only if you can join us immediately or serving notice period.

Location:

B3, Office number 406, Dubai Commercity, Umm ramool, Al Rashidiya, Dubai, UAE.

Job Types: Full-time, Permanent

Pay: Up to AED10,000.00 per month