Sr. AI Engineer

Title: AI Engineer

Location: Hyderabad

Job Type: Full-Time

Experience: 10+ Years

Job Overview

We are seeking a highly experienced AI Engineer to lead the design, development, and delivery of enterprise-scale Generative AI and Machine Learning solutions. The ideal candidate will have strong hands-on expertise in LLMs, RAG, agentic AI, conversational AI, Azure OpenAI, Azure AI Foundry, and modern AI/ML engineering practices .

This role will work closely with engineering teams, product leaders, architects, and business stakeholders to translate business requirements into secure, scalable, and production-ready AI solutions.

Key Responsibilities

• Architect, design, and deliver scalable Generative AI and Machine Learning solutions across the full project lifecycle, from proof of concept and experimentation through production deployment and optimization.
• Design and build enterprise-grade conversational AI platforms , including RAG-based applications and agentic workflows using Azure OpenAI, Azure AI Foundry, and Azure AI services .
• Apply advanced prompt engineering, embeddings, vector search, fine-tuning, context management, and tool/function calling techniques to optimize LLM-based solutions.
• Design and implement AI/ML systems with feedback loops, automated retraining, evaluation, and fine-tuning pipelines to continuously improve model accuracy and relevance.
• Implement Retrieval-Augmented Generation (RAG) architectures to ensure AI responses are accurate, contextual, and grounded in approved enterprise data sources.
• Build and maintain CI/CD pipelines, observability, monitoring, and lifecycle management for AI/ML and LLM workloads in production.
• Stay current with advancements in LLMs, agentic AI, and AI orchestration , including few-shot learning, structured outputs, Model Context Protocol (MCP), and modern Agent SDKs/frameworks.
• Define AI success metrics aligned with business objectives and continuously evaluate and improve model quality, accuracy, latency, reliability, and overall system performance .
• Establish enterprise AI design standards, reference architectures, development patterns, and best practices .
• Ensure AI solutions meet enterprise requirements for security, reliability, scalability, governance, compliance, and responsible AI .
• Evaluate, prototype, and adopt emerging AI frameworks, architectures, tools, and Azure capabilities.
• Develop and support frontend integrations for conversational AI and chat experiences across web applications, Microsoft Teams, and Copilot experiences .
• Provide technical leadership and mentorship to senior and junior engineers while establishing a high standard for engineering excellence.
• Partner with product managers, enterprise architects, engineering teams, and business stakeholders to translate business requirements into scalable AI solutions.
• Communicate complex AI concepts, technical approaches, and architectural decisions effectively to both technical and non-technical audiences.

Required Qualifications

• 10+ years of progressive experience in software engineering, data engineering, big data, or related technology roles.
• 5+ years of hands-on experience in AI/ML , with strong expertise in applied machine learning and AI engineering.
• Advanced knowledge of Machine Learning, Natural Language Processing (NLP), Generative AI, and Large Language Models (LLMs) .
• Strong practical experience integrating, optimizing, evaluating, and deploying LLM-based applications in enterprise environments.
• Proven experience with prompt engineering, context management, embeddings, vector databases/vector search, RAG, and retrieval strategies .
• Demonstrated experience designing and delivering enterprise-scale chatbots, conversational AI platforms, virtual assistants, or AI agents .
• Strong hands-on experience with Azure OpenAI, Azure AI Foundry, Azure AI Services , and related Azure cloud capabilities.
• Experience with AI agents, agentic workflows, tool/function calling, and AI orchestration frameworks .
• Strong experience building CI/CD pipelines and deploying AI workloads using Docker and Kubernetes .
• Experience with ML lifecycle and experiment-management tools such as MLflow or equivalent platforms .
• Strong programming skills in *…