Sr. AI Engineer

TEK Analytics

Hyderabad

On-site

INR 4,500,000 - 7,500,000

Full time

6 hours ago
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Job summary

TEK Analytics seeks an experienced AI Engineer to lead enterprise-scale Generative AI and ML initiatives. You will architect, design, and deliver AI solutions spanning POC to production, including chat platforms and RAG-based workflows.

The role requires deep expertise in Azure OpenAI, LLMs, and AI orchestration, with strong Python skills and a track record in implementing secure, scalable AI systems for enterprise customers.

Qualifications

  • 10+ years of progressive experience in software/AI related roles.
  • 5+ years of hands-on AI/ML experience with enterprise deployments.
  • Strong knowledge of ML, NLP, GenAI and LLMs.
  • Experience deploying LLM-based apps in enterprise environments.
  • Experience with prompt engineering, embeddings, vector search, RAG and retrieval strategies.
  • Experience designing enterprise-scale chatbots/AI agents.
  • Hands-on with Azure OpenAI and related Azure services.
  • Experience CI/CD pipelines and deploying AI workloads with Docker/Kubernetes.
  • Strong programming skills in Python and modern AI/ML frameworks.
  • Knowledge of AI governance, bias mitigation, explainability, and compliance.

Responsibilities

  • Architect and deliver scalable Generative AI and ML solutions across full project lifecycle.
  • Design enterprise-grade conversational AI platforms with RAG and agentic workflows.
  • Apply prompt engineering, embeddings, vector search, fine-tuning, and context management.
  • Build AI/ML systems with feedback loops, retraining, evaluation, and fine-tuning pipelines.
  • Implement RAG architectures to ensure accurate, contextual responses from enterprise data.
  • Maintain CI/CD, observability, monitoring for AI/LLM workloads in production.
  • Stay updated with LLMs, agentic AI, and AI orchestration advancements.
  • Define AI success metrics and improve model quality and reliability.
  • Establish AI design standards, reference architectures, and best practices.
  • Ensure security, reliability, scalability, governance and responsible AI.

Skills

Python
Leadership
Communication
Problem solving

Tools

Azure OpenAI
Azure AI Foundry
Azure AI Services
Docker
Kubernetes
Pinecone
Weaviate

Job description

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 Python and experience with modern AI/ML development frameworks.
  • Solid understanding of AI governance, responsible AI, bias mitigation, explainability, model evaluation, and compliance.
  • Strong knowledge of cloud security, Microsoft Entra ID (Azure AD), identity and access management, data governance, and enterprise risk controls.
  • Experience leading or significantly contributing to large-scale AI modernization, digital transformation, or enterprise GenAI initiatives.
  • Strong understanding of production AI requirements including scalability, reliability, observability, performance, security, and cost optimization.
Preferred Qualifications
  • Experience implementing MCP (Model Context Protocol) and modern agent frameworks/SDKs.
  • Experience with Azure AI Foundry Agent Service or comparable enterprise agent platforms.
  • Experience with vector databases such as Azure AI Search, Pinecone, Weaviate, or similar technologies.
  • Experience with LLM evaluation frameworks and automated quality assessment.
  • Experience implementing LLM observability and production monitoring.
  • Familiarity with Microsoft Copilot and Microsoft Teams integrations.
  • Experience with fine-tuning techniques such as LoRA/PEFT and model optimization.
  • Experience working with enterprise data platforms, APIs, and modern cloud architectures.
  • Strong communication, leadership, problem-solving, and stakeholder-management skills.
Technical Skills

AI / GenAI: Generative AI, LLMs, NLP, RAG, Agentic AI, AI Agents, Prompt Engineering, Fine-Tuning, Embeddings, Vector Search, Function Calling, Structured Outputs, MCP

Programming & Frameworks: Python, AI/ML Frameworks, Agent SDKs, AI Orchestration Frameworks

Integrations: Web Chat Interfaces, Microsoft Teams, Microsoft Copilot, REST APIs

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