Summary
AppliedAI is an Abu Dhabi-based AI technology company working on solutions for regulated industries. The Senior AI Engineer will design and improve Opus’s AI serving, orchestration, workflow and agent systems, with a focus on reliability, latency and quality. The role includes guiding prompt alignment, building monitoring and error-tracking systems, leading design reviews, and mentoring engineers. Applicants should have 3–5 years of ML engineering experience, strong Python skills, and experience with model serving, orchestration tools and observability. The position is on-site at AppliedAI’s Abu Dhabi headquarters.
The posting
As published on appliedai.com. Pulled from the employer's site and shown as they wrote it.
Senior AI Engineer
On-site | Abu Dhabi
AppliedAI is a pioneering AI technology company headquartered in Abu Dhabi, committed to innovation and excellence in artificial intelligence solutions in regulated industries such as healthcare, insurance, government, and financial services.
Opus is the world's first Knowledge Work AI platform. Built by AppliedAI to pioneer Supervised Automation, a human-in-the-loop model where AI handles repetitive, structured tasks while human experts provide crucial oversight at defined intervals.
The platform uses its proprietary Large Work Model to generate and orchestrate outcome-based workflows, enabling a dramatic reduction in the cost of knowledge work and allowing human talent to focus on high-value, creative, and judgement-intensive activities.
Role Overview:
As a Senior AI Engineer, you’ll play a key role in the design, evolution, and delivery of Opus’s end-to-end AI infrastructure, spanning model serving, orchestration, prompt alignment, workflow intelligence, and agent systems.
Your mission is to ensure that every AI-powered feature across the platform operates with reliability, clarity, and measurable excellence in both performance and user experience.
You will guide a multidisciplinary UAE-based team of engineers working across model pipelines, workflow representations, and agentic frameworks. Together, you will refine the systems that connect foundational models, structured process data, and real-world user interactions.
Key Responsibilities:
Design and evolve high-performance AI serving and orchestration pipelines.
Refactor existing systems for clarity, modularity, and maintainability.
Improve runtime latency, reliability, and quality metrics across live AI features.
Build observability and error-tracking layers to detect regressions before they reach users.
Guide prompt and alignment strategies, ensuring consistent model behavior and semantic fidelity across all user-facing features.
Collaborate with product teams to ensure AI responses meet quality, stability, and response-time targets.
Uphold engineering standards across performance, documentation, and code quality.
Lead design reviews, incident analysis, and optimization cycles across Opus AI modules.
Qualifications:
3-5 years in ML engineering, ideally within a SaaS / Product organisation.
Expert in Python.
Strong background in real-time model serving, orchestration (Airflow, Celery, Kubernetes), and observability systems.
Familiarity with LLM pipelines, workflow modeling, and agent-based AI frameworks.
Experience deploying and optimizing inference pipelines (e.g. LLMs, CV or similar APIs).
Skilled in monitoring, benchmarking, and system observability.
Experience mentoring engineers and managing cross-functional delivery cycles.
Proven ability to translate complex AI systems into reliable, scalable, and high-quality user-facing products.
Experience improving LLM response consistency and user-facing reliability.
Bonus: Experience building and deploying chatbots or conversational AI systems that integrate LLMs, APIs, and user interaction flows.
Why join AppliedAI:
Opportunity to work with a highly innovative AI technology company.
Collaborative and innovative work environment.
Growing, entrepreneurial and forward-thinking culture.
Career growth and professional development opportunities.
Exposure to a thriving ecosystem working from our Abu Dhabi HQ.