Data Engineer at INCEPTION ARTIFICIAL INTELLIGENCE L.L.C - O.P.C

, , -

Full Time

Start Date

Immediate

Expiry Date

18 Apr, 26

Salary

0.0

Posted On

18 Jan, 26

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Python, SQL, PySpark, ML/AI Frameworks, Azure Agent Foundry, OpenAI APIs, RAG Systems, Vector Databases, Azure Databricks, Big Data Tools, Data Modeling, ETL, Data Quality, REST APIs, GraphQL APIs, Docker, Kubernetes

Industry

technology;Information and Internet

Description

Overview: We are looking for a Data Engineer who can build scalable data pipelines while also developing intelligent AI solutions using Azure Agent Foundry, OpenAI services, LangChain, Databricks, and modern cloud architectures. The ideal candidate has strong data engineering foundations combined with hands-on experience designing and deploying enterprise-grade AI systems. Inception is the UAE’s national-scale enabler in AI Research and Development. Partnering with Microsoft's AI SaaS, we offer domain-specific Agentic AI Orchestrator platforms utilizing reasoning agents for precise and cost-effective services. Our focus includes AI incubation, IP creation, applied AI R&D, and AI investment products. By creating models tailored to specific domains and languages, we ensure superior accuracy and efficiency. Collaborating with top universities and industry giants to drive significant advancements in AI technology within the region. Responsibilities: Develop and deploy AI agents using Azure Agent Foundry, OpenAI, LangChain, and N8N. Build RAG pipelines, embeddings, vector database integrations, and knowledge graph solutions. Design and maintain scalable data pipelines, ETL/ELT workflows, and data architectures. Build and maintain APIs and data services supporting AI and analytics workloads.Optimize ML workflows on Azure Databricks and integrate with Azure Fabric. Ensure data quality, reliability, governance, and compliance across all systems. Collaborate with data scientists, ML engineers, and product teams to deliver intelligent features. Support MLOps and DevOps processes including CI/CD, model lifecycle management, and containerized deployments. Qualifications: Required Skills Strong proficiency in Python, SQL, PySpark, and ML/AI frameworks. Experience with Azure Agent Foundry, OpenAI APIs, LLMOps, RAG systems, and vector databases. Hands-on experience with Azure Databricks, Azure cloud services, and data platforms.Knowledge of big data tools (Spark, Hadoop, Flink) and modern data storage (SQL, NoSQL). Experience with REST/GraphQL APIs, Kafka/RabbitMQ, Docker/Kubernetes. Solid understanding of data modeling, ETL, and data quality best practices.Strong problem-solving, communication, and cross-functional collaboration skills. Qualifications Bachelor’s in Computer Science, Engineering, Data Science, or related field. 3+ years experience in Data Engineering, AI Engineering, or ML Engineering roles. Experience delivering scalable AI/data solutions in cloud environments (Azure preferred). What we look for If you are a performance-driven, inquisitive mind with the agility to adapt to ambiguity, you will fit right in. You should be eager to explore opportunities to build meaningful collaborations with stakeholders and aspire to create unique customer-centric solutions. Bias for action and a passion to conquer new frontiers in the AI space is at the heart of the Inception community. What working at Inception offers Culture: An open, diverse and inclusive environment with a global vision that encourages personal growth and focuses on ground-breaking, industry-first innovations. Career: Outstanding learning, development & growth opportunities via structured training programs and innovative, high-tech projects. Work-Life: A hybrid work policy to strike the perfect balance between office and home. Rewards: A competitive remuneration package with a host of perks including healthcare, education support, leave benefits and more. If you can confidently demonstrate that you meet the criteria above, please contact us as soon as possible.

Responsibilities

Develop and deploy AI agents and build scalable data pipelines. Collaborate with data scientists and ML engineers to deliver intelligent features and ensure data quality across systems.