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Selected role

Senior AI Engineer

DICETEK LLC Abu Dhabi, AZ, AE

Senior Full-time

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. This role includes building intelligent systems that integrate complex backend services and client-facing applications across web, mobile, and enterprise platforms.

The primary responsibility will be 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. Thus, a commitment to collaborative problem solving, sophisticated design, and product quality is essential.

KEY ACCOUNTABILITIES:

Designing and building Generative AI applications using Large Language Models (LLMs)
Developing Agentic AI solutions, including autonomous agents, multi-agent orchestration, and workflow-driven decision systems
Building solutions using frameworks such as LangChain, LangGraph or similar agent frameworks
Implementing RAG architecture with vector databases
Knowledge of embeddings, vector DBs, and model evaluation.
Implement various Context Engineering strategies to reduce Token Utilization & Latency.
Implement RAG Strategies to reduce retrieval latency and answer relevancy.
Prompt engineering, tool calling, memory management, and agent orchestration
Integrating AI services with enterprise APIs, middle ware, and backend systems
Evaluated & Improvise AI Agent Performance using several metrics
Deploying scalable AI solutions on Azure / AWS cloud platforms
Working with model evaluation, guardrails, observability, and AI governance

QUALIFICATIONS & EXPERIENCE:

Bachelor’s degree in computer science, Engineering, or a related field.
Senior professional with around 10 years of experience.
3+ years of relevant experience in AI Engineering
Working experience in an agile software development environment with a good understanding of the principles of agile architecture. Strong collaborative mindset for collective decentralized decision making.
Demonstrate strong technical skills with a deep understanding of modern architectural styles and practices such as Microservices, Containers, Cloud (AWS, Azure), APIs, Continuous Delivery, Event-driven architecture, Evolutionary architecture, etc., with a passion for hands on coding.
Strong foundation knowledge of software architecture concepts, patterns, principles, and quality attributes. Ability to consistently apply them in real-world scenarios with a pragmatic, system thinking, and problem-solving mindset by analyzing architecture trade-offs for delivering high-quality, sustainable solution architecture.
Proven leadership skills with a proactive, positive, and growth mindset. Ability to foster and motivate programmers for delivering with craftsmanship. Good personal skills to continuously engage and communicate with an egoless empathetic mindset.
Experience and expertise in delivering architecture for large software solutions meeting critical business purposes. Ability to proactively discover technical debts and continuous improvement opportunities of existing live systems. Work closely with the product owner and enterprise architects to influence and prioritize technical backlog items.
Strong proficiency in Python (NumPy, pandas, FastAPI, PyTorch/TensorFlow).
Experience with Agent framework LangChain, Lang Graph.
Architect end-to-end data indexing pipelines optimized for semantic search and RAG.
Design resilient data ingestion frameworks that ensure high availability and low latency for vectorized datasets.
Experience deploying and managing models via Amazon Bedrock, Azure OpenAI Service, and Google Vertex AI.
Integration of pre-built AI APIs for Speech-to-Text, Computer Vision, and Natural Language Processing (NLP).
Leveraging serverless architectures (e.g., AWS Lambda, Azure Functions) to trigger AI inference and data pre-processing.
Experience working with CI/CD tools like Jenkins/Gitlab in Cloud Native environments.
Experience in setting up pipeline for cloud based and on-prem based application with static code analysis, requirement tagging in Jira.
Experience working with one or more DevOps tools & config management tools.
Experience in managing and deploying AI workloads in Kubernetes.
Experience operating monitoring tools for traditional and cloud environments.
Strong analytical mind for problem solving.

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