G42Data Engineer
AI in this role
Inception42, a G42 company, is the region’s leading innovator of AI-powered domain-specific as well as industry-agnostic products, built on a rich heritage of research and development. Within the G42 ecosystem, Inception functions as the core intelligence layer – transforming data and compute infrastructure into real-world, applied AI solutions. Beyond its commercial endeavors, Inception is committed to creating positive societal impact. For more information, please visit www.inception42.ai
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.
Responsibilities:
What You’ll Own- 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:
What We’re Looking For- 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).
- 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.
What We Look ForIf 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 Inception42 community. What Working At Inception42 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.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.
How we rate this
Data Engineer at G42 rates 87 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.
Builds AI. The job is building AI systems.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Open the description and count.
Prepare for this job
A free preview built only from this posting: what it asks for, what you could be asked in an interview, and how to adjust your resume.
Skills and AI tools this role asks for
Questions you could be asked
- How would you design a retrieval step so the model answers from real data instead of guessing?
- How do you decide when an AI agent can act on its own versus asking for approval first?
- How do you monitor a model once it's live, and how do you know it needs retraining?
- What's a project where you used OpenAI hands-on?
- Walk me through how you've used LangChain in your day-to-day work.
Adapt your resume
- List these exact terms on your resume: RAG, AI Agents, ML Ops, OpenAI, and LangChain. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them — a tool named with nothing behind it rarely survives a human read.
- Lead with what you built, trained or shipped — this role is judged on the AI system itself, not the tools around it.
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