Artificial Intelligence (AI) Engineer

Dicetek LLC; Abu Dhabi; On-site; AED 350,000 - 550,000; Full time

Job summary

Dicetek LLC in Abu Dhabi seeks a senior AI Engineer with around 10 years in software engineering, architecture or cloud platforms and at least 3 years hands-on AI engineering, including Generative AI and LLM-based delivery. Proficiency in Python, PyTorch or TensorFlow, and experience with LangChain, Semantic Kernel and AutoGen are essential.

The role requires deploying AI workloads on Kubernetes, cloud-native services, and robust CI/CD pipelines, with strong collaboration across product and

Qualifications

• Bachelor's degree in a related discipline is required.
• Minimum 10 years total software engineering/architecture/cloud experience; at least 3+ years in AI engineering with Generative AI/LLMs.
• Strong Python proficiency with PyTorch or TensorFlow; hands-on with LangChain, LangGraph, Semantic Kernel and AutoGen.

Skills

Generative AI

LLMs

LangChain

LangGraph

Semantic Kernel

AutoGen

Python

PyTorch

TensorFlow

FastAPI

Kubernetes

CI/CD

Jenkins

GitLab

REST APIs

Microservices

Cloud platforms (Azure, AWS, GCP)

Embeddings / RAG

Observability / monitoring

Education

Bachelor’s degree in Computer Science, Software Engineering, Information Technology, Data Science, Artificial Intelligence or related discipline

Cloud, AI engineering or architecture certifications

Tools

NumPy

pandas

FastAPI

Jira

Job description

Minimum Qualification

• Bachelor’s degree in Computer Science, Software Engineering, Information Technology, Data Science, Artificial Intelligence or a related discipline.
• Relevant cloud, AI engineering, machine learning or architecture certifications are preferred.

Minimum Experience :-

• Senior professional with around 10 years of total software engineering, architecture, cloud or platform engineering experience.
• Minimum 3+ years of relevant hands‑on AI Engineering experience, including Generative AI and practical LLM-based application delivery.
• Strong proficiency in Python, including NumX, pandas, FastAPI and hands‑on experience with PyTorch or TensorFlow.
• Hands‑on experience with LangChain and LangGraph; mandatory working experience with Microsoft Semantic Kernel and Microsoft AutoGen.
• Experience implementing RAG using embeddings, vector databases, semantic search, retrieval optimization and model evaluation techniques.
• Experience deploying and managing models using Amazon Bedrock, Azure OpenAI Service and Google Vertex AI.
• Hands‑on experience with microservices, containers, APIs, event‑driven architecture, cloud‑native services and evolutionary architecture practices.
• Experience managing and deploying AI workloads on Kubernetes in cloud‑native and/or hybrid environments.
• Experience with CI/CD tools such as Jenkins or GitLab, DevOps toolchains, configuration management and cloud/on‑prem deployment pipelines.
• Experience setting up pipelines with static code analysis, requirement tagging in Jira, quality gates and release governance.
• Experience operating monitoring tools for traditional infrastructure, cloud environments and AI‑enabled business applications.
• Strong hands‑on problem‑solving mindset with the ability to analyze trade‑offs and deliver sustainable, secure and high‑quality solutions.

Key Technical Skills

• Generative AI, Agentic AI, autonomous agents, multi‑agent orchestration and workflow‑based AI systems.
• LLMs, embeddings, vector databases, RAG, semantic search, model evaluation, guardrails, observability and AI governance.
• Semantic Kernel, AutoGen, LangChain, LangGraph and similar agent frameworks.
• Python, FastAPI, PyTorch/TensorFlow, REST APIs, microservices, serverless functions and event‑driven integration.
• Azure, AWS, Kubernetes, containers, CI/CD, DevOps automation, monitoring and secure software delivery.

Behavioural / Leadership Skills

• Strong collaborative mindset for agile architecture and decentralized decision making.
• Proactive, positive and growth‑oriented leadership style with the ability to motivate engineers and foster craftsmanship.
• Strong communication, stakeholder engagement and influencing skills across product, business, architecture and engineering teams.
• Analytical, system‑thinking and pragmatic problem‑solving approach with commitment to product quality.