**HIRING**
I am working with a customer in Abu Dhabi who are looking for an MLOps/LLM Ops Engineer, on a 1-year contract, with the view to extend, or go Permanent.
This role will be onsite in Abu Dhabi and requires you to be in the office.
Job Title - Ai Engineer
Salary - AED 27,000-AED 28,000 Per Month
Contract Length - 1 Year (Extendable)
Location - Abu Dhabi
Start Date - ASAP
The client I am working with are a specialist AI and data consultancy with extensive experience implementing intelligent enterprise systems across multiple industries, with particular depth in financial services and banking.
The MLOps and LLMOps Engineer is a specialized technical role focused on bridging the gap between AI development and production-grade operations. You will design, deploy, and manage scalable AI solutions primarily across AWS and Azure environments, integrating Machine Learning Operations (MLOps) and Large Language Model Operations (LLMOps). By leveraging containerization, automated CI/CD pipelines, and robust data engineering, you will ensure that the clients AI-driven applicationsincluding Generative AI and LLM agentsare secure, efficient, compliant, and highly available.
Responsibilities
- Design and deploy scalable AI infrastructure using GitHub Actions, EKS, ECS, and AWS Lambda; automate all resource provisioning via Terraform.
- Create and manage end-to-end CI/CD pipelines for model deployment, versioning, and lifecycle management using Azure DevOps and GitHub Actions.
- Deploy machine learning and large language models via Amazon SageMaker, EKS, and Azure ML Endpoints.
- Implement comprehensive monitoring for model performance and drift using Amazon CloudWatch, SageMaker Model Monitor, and OpenSearch.
- Integrate advanced services including Azure OpenAI, Azure Cognitive Services, and AWS Rekognition into enterprise workflows.
- Design robust data pipelines and real-time ingestion streams using AWS Glue, Amazon Redshift, Athena, and Apache Spark.
- Enforce cloud security through AWS WAF, Azure Key Vault, and RBAC, ensuring all deployments meet GDPR and ISO compliance standards.
- Supervise team activities and contribute to change initiatives in line with the Bank's continuous improvement standards.
- Supporting, Coaching and Mentoring more junior members of the team, when required
- Additional responsibilities on occasion, on management request
Qualifications/Relevant Experience:
- Minimum of 5 years in designing and deploying AI solutions in cloud environments, specifically within MLOps/LLMOps frameworks.
- Azure and/or AWS certifications (e.g., AWS Certified Machine Learning - Specialty or Azure AI Engineer Associate) are highly preferred.
- Proficient with GitHub Actions, Spark, Redshift, MongoDB, and Azure Purview.
Essential Capabilities:
- Deep hands-on expertise in AWS (SageMaker, EKS, S3) and Azure (OpenAI, Cognitive Services) ecosystems.
- Mastery of Terraform for multi-cloud resource automation.
- Proven experience in both MLOps (standard ML) and LLMOps (Large Language Models), focusing on fine-tuning, orchestration, and monitoring.
- Expertise in managing container images via ECR/ACR an
Desired Capabilities/Experience:
- Ability to seamlessly manage workloads that span across both AWS and Azure.
- Skill in communicating complex technical infrastructure requirements to non-technical business stakeholders.
- Adaptability in troubleshooting model drift and performance bottlenecks in real-time agentic workflows.
- Proactive identification of new tools (e.g., Vector DBs, orchestration frameworks) to improve deployment velocity.
Thanks,
Ollie
