AI Engineer – Generative AI & Agentic AI

Dicetek LLC; Abu Dhabi; On-site; AED 320,000 - 520,000; Full time

Job summary

Dicetek LLC is seeking an experienced AI Engineer to design, develop and deploy Generative AI and Agentic AI solutions for enterprise-scale use cases. You will build intelligent systems that integrate backend services and client applications across web, mobile, and enterprise platforms.

You will lead the implementation of autonomous agents, multi-agent workflows, and governance in cloud-native environments, collaborating with architecture, engineering, product, and business teams to deliver

Qualifications

• 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.

Responsibilities

• Design and deploy Generative AI and Agentic AI solutions for enterprise-scale use cases across web, mobile and enterprise platforms.
• Build intelligent systems integrating complex backend services and client-facing applications and coordinate with cross-functional teams.
• Deliver secure, scalable, observable and governed AI solutions in cloud-native environments.

Skills

Python

NumPy/Pandas

FastAPI

PyTorch/TensorFlow

LangChain

LangGraph

Semantic Kernel

AutoGen

Kubernetes

CI/CD (Jenkins/GitLab)

REST APIs

Model Deployment

Education

Bachelor's degree in Computer Science, Software Engineering, IT, Data Science, AI or related discipline

Tools

LangChain

LangGraph

Semantic Kernel

AutoGen

Kubernetes

Jenkins

GitLab

REST APIs

Job description

We are looking for an experienced AI Engineer responsible for designing developing and deploying Generative AI and Agentic AI solutions that support enterprise-scale business use cases The role will build intelligent systems that integrate complex backend services and client-facing applications across web mobile and enterprise platforms The primary responsibility is to design and develop AI-powered applications autonomous agents and multi-agent workflows while coordinating with cross-functional teams across architecture engineering product and business functions A commitment to collaborative problem solving sophisticated design and product quality is essential This role requires strong hands-on engineering experience practical working knowledge of modern agent frameworks and the ability to deliver secure scalable observable and governed AI solutions in cloud-native environments

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.

Technical Proficiency

• Strong proficiency in Python, including NumPy, 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.

Skills

Generative AIPythonKubernetes