AI Engineer
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Key skills for this role
About the Role
Tata Consultancy Services (TCS) is seeking an AI Engineer to design, build, and deploy AI-powered applications using Azure AI Services. The role involves LLM integration, RAG pipelines, agentic AI development, and production deployment.
Key Skills for This Role
Responsibilities
- Design, build, and deploy AI powered applications using Azure AI Services, including Azure OpenAI Service, Azure Machine Learning, Azure Cognitive Services, Azure AI Search, Azure Functions, and Azure Databricks
- Develop and integrate Large Language Model (LLM) solutions using Azure OpenAI endpoints (GPT 4.1, GPT 4o, GPT 4o mini) routed through FAB's centralized AI Hub gateway for governance, observability, and capacity management
- Write clean, modular, and production grade Python code for AI/ML model development, API integrations, data processing pipelines, backend services, and automation workflows using frameworks such as LangChain, LlamaIndex, Semantic Kernel, LangGraph, and FastAPI
- Implement Retrieval Augmented Generation (RAG) pipelines, embeddings, vector search, semantic retrieval architectures, prompt engineering, and evaluation techniques for enterprise knowledge mining and document intelligence
- Design and develop intelligent agentic AI systems capable of planning, reasoning, tool execution, and orchestration across enterprise systems using FAB's GERNAS OS platform and Agent Development Kit (ADK) in a secure and governed manner
- Implement model evaluation metrics for accuracy, hallucination detection, bias, latency, and throughput in alignment with FAB's Responsible AI framework
- Deploy, monitor, and optimize AI solutions in production environments using CI/CD practices, containerization, observability, logging, performance monitoring, and cost optimization techniques
- Collaborate with data scientists, platform engineers, DevOps/MLOps engineers, business analysts, and product teams to convert business requirements into scalable AI solutions
- Continuously evaluate emerging Azure AI, Generative AI, and Agentic AI capabilities and recommend practical adoption opportunities aligned with FAB's AI strategy
Requirements
- Bachelor's degree in Computer Science, Engineering, Artificial Intelligence, Data Science, Mathematics, Statistics, or related field
- 3+ years of hands on experience in designing, developing, and deploying AI/ML or Generative AI solutions in production environments
- Mandatory hands on experience with Microsoft Azure AI Services
- Strong proficiency in Python programming, including experience with REST APIs, SDKs, asynchronous processing, data manipulation, backend development, and AI application frameworks (LangChain, LlamaIndex, Semantic Kernel, LangGraph, FastAPI)
- Deep understanding of machine learning, statistical modeling, NLP, generative AI principles, LLM application development, prompt engineering, RAG architecture, embeddings, vector databases, semantic search, and model evaluation techniques
- Advanced proficiency in ML libraries such as PyTorch, TensorFlow, Hugging Face Transformers, scikit learn, and NLP libraries (spaCy, NLTK)
- Experience with vector databases including FAISS, Azure AI Search, ChromaDB, and Pinecone
- Hands on experience with DevOps/MLOps practices and tools such as Git, Docker, Kubernetes, CI/CD pipelines, MLflow, Terraform, Azure Monitor, and Application Insights
- Understanding of cloud security, identity and access management, data privacy, encryption, logging, monitoring, and secure API integration patterns
- Awareness of ethical considerations and responsible AI practices, including fairness, accountability, transparency, bias detection, hallucination mitigation, and compliance in AI systems
Full Job Posting
Job Description
- Tata Consultancy Services (TCS) is an IT services, consulting and business solutions organization.
- We are looking for an AI Engineer to join our team in Dubai.
Key Accountabilities
- AI Solution Design & Development: Design, build, and deploy AI powered applications using Azure AI Services.
- LLM Integration & Generative AI: Develop and integrate Large Language Model (LLM) solutions using Azure OpenAI endpoints.
- Python Engineering & Backend Development: Write clean, modular, and production grade Python code for AI/ML model development.
- RAG & Semantic Retrieval: Implement Retrieval Augmented Generation (RAG) pipelines, embeddings, vector search.
- Agentic AI Development: Design and develop intelligent agentic AI systems capable of planning, reasoning, tool execution.
- Model Evaluation & Responsible AI: Implement model evaluation metrics for accuracy, hallucination detection, bias.
- Deployment & Production Operations: Deploy, monitor, and optimize AI solutions in production environments.
- Collaboration & Stakeholder Engagement: Collaborate with data scientists, platform engineers, DevOps/MLOps engineers.
- Innovation & Continuous Learning: Continuously evaluate emerging Azure AI, Generative AI, and Agentic AI capabilities.
Technical Skills
- Azure AI Services: Demonstrated working experience with Microsoft Azure AI Services including Azure OpenAI, Azure Machine Learning, Azure Cognitive Services, Azure AI Search, Azure Functions, and Azure Databricks.
- Python Programming: Strong proficiency in Python programming, including experience with REST APIs, SDKs, asynchronous processing, data manipulation, backend development, and AI application frameworks (LangChain, LlamaIndex, Semantic Kernel, LangGraph, FastAPI).
- LLM & Generative AI: Deep understanding of machine learning, statistical modeling, NLP, generative AI principles, LLM application development, prompt engineering, RAG architecture, embeddings, vector databases, semantic search, and model evaluation techniques.
- ML Libraries & Frameworks: Advanced proficiency in ML libraries such as PyTorch, TensorFlow, Hugging Face Transformers, scikit learn, and NLP libraries (spaCy, NLTK).
- Vector Databases: Experience with vector databases including FAISS, Azure AI Search, ChromaDB, and Pinecone.
- DevOps/MLOps: Hands on experience with DevOps/MLOps practices and tools such as Git, Docker, Kubernetes, CI/CD pipelines, MLflow, Terraform, Azure Monitor, and Application Insights.
- Cloud Security & Integration: Understanding of cloud security, identity and access management, data privacy, encryption, logging, monitoring, and secure API integration patterns.
- AI Ethics & Governance: Awareness of ethical considerations and responsible AI practices, including fairness, accountability, transparency, bias detection, hallucination mitigation, and compliance in AI systems.
Knowledge, Skills, & Experience
- Minimum Qualifications: Bachelor's degree in Computer Science, Engineering, Artificial Intelligence, Data Science, Mathematics, Statistics, or related field; Master's degree is preferred. Microsoft Certified: Azure AI Engineer Associate (AI 102) certification is highly preferred.
- Minimum Experience: 3+ years of hands on experience in designing, developing, and deploying AI/ML or Generative AI solutions in production environments.
- Mandatory hands on experience with Microsoft Azure AI Services.
- Experience working with large scale datasets and real time enterprise data.
- Experience in financial services, banking, risk, compliance, customer service, or regulated enterprise environments is an advantage.
Application Deadline
- Application Deadline: 30 July 2026
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