Role Overview

We are looking for an experienced Senior AI Engineer / Lead AI Engineer with 10+ years of overall technology experience and strong hands-on expertise in AI/ML, Generative AI, LLMs, RAG, Agentic AI, Python, and Cloud.

The candidate will be responsible for architecting, developing, deploying, and scaling enterprise-grade AI solutions and should be capable of taking AI initiatives from concept and architecture through production deployment and optimization.

The role requires a strong combination of hands-on engineering, solution architecture, technical leadership, and stakeholder management.

Key Responsibilities

- Architect and develop scalable AI/ML and Generative AI solutions for enterprise use cases.
- Design and implement LLM-powered applications, RAG systems, AI agents, and multi-agent architectures.
- Build production-grade Agentic AI workflows involving reasoning, planning, tool/function calling, memory, orchestration, and enterprise API integration.
- Design end-to-end RAG architectures, including document ingestion, chunking, embeddings, vector search, hybrid search, retrieval optimization, re-ranking, and response generation.
- Work with LLMs such as OpenAI, Azure OpenAI, Anthropic, Gemini, Llama, Mistral, or equivalent models.
- Implement advanced Prompt Engineering and Context Engineering techniques.
- Develop AI applications using LangChain, LangGraph, LlamaIndex, Semantic Kernel, AutoGen, CrewAI, or equivalent frameworks.
- Design and integrate Vector Databases / Vector Search solutions.
- Develop scalable AI APIs and microservices using Python, FastAPI, Flask, or equivalent technologies.
- Integrate AI solutions with enterprise applications, databases, APIs, and data platforms.
- Establish LLM evaluation and testing frameworks for accuracy, grounding, hallucination, relevance, safety, latency, and cost.
- Implement AI security, governance, guardrails, access control, data privacy,



and responsible AI practices.
- Deploy and operate AI solutions across Azure/AWS/GCP cloud environments.
- Drive production readiness, including CI/CD, Docker, monitoring, logging, observability, scalability, and performance optimization.
- Optimize AI systems for latency, throughput, reliability, model performance, and infrastructure cost.
- Evaluate emerging AI technologies and identify opportunities for enterprise adoption.
- Lead technical discussions with architects, engineering teams, product teams, and business stakeholders.
- Mentor senior and junior engineers and establish engineering best practices.
- Conduct technical reviews and ensure adherence to architecture, coding, security, and development standards.
- Build reusable AI frameworks, accelerators, components, and reference architectures.

Mandatory Skills

- 10+ years of overall experience in Software Engineering / AI / ML / Data Science / Technology.
- Strong hands-on Python development experience.
- Strong hands-on experience in AI/ML engineering.
- Strong experience with Generative AI and Large Language Models (LLMs).
- Proven experience designing and implementing RAG architectures.
- Strong experience with Agentic AI / AI Agents / Multi-Agent Systems.
- Robust Prompt Engineering / Context Engineering experience.
- Experience with LLM orchestration frameworks such as LangChain, LangGraph, LlamaIndex, Semantic Kernel, AutoGen, or CrewAI.
- Experience with OpenAI / Azure OpenAI / Anthropic / Gemini / open-source LLMs.
- Strong experience with Vector Databases and semantic search.




- Experience building REST APIs / microservices using FastAPI or Flask.
- Strong knowledge of Machine Learning / Deep Learning concepts.
- Experience deploying AI solutions on AWS / Azure / GCP.
- Strong understanding of AI system architecture, distributed systems, scalability, and system design.
- Experience with Docker, Git, CI/CD, testing, monitoring, and production support.
- Strong technical leadership and stakeholder-management skills.

Good to Have

- MCP / Model Context Protocol experience.
- Experience with LLM evaluation and observability tools such as LangSmith, RAGAS, Promptfoo, or equivalent.
- Experience with fine-tuning, SFT, LoRA, QLoRA, PEFT, RLHF/DPO.
- Knowledge of GraphRAG, Knowledge Graphs, Neo4j, or semantic search.
- Experience with MLflow, Kubeflow, SageMaker, Azure ML, or equivalent MLOps platforms.
- Experience with AWS Bedrock / Azure AI Foundry / Vertex AI.
- Experience with LLM gateways, model routing, caching, and cost optimization.
- Experience with real-time AI / streaming architectures.
- Experience with Kafka, SQS, RabbitMQ, or event-driven architectures.
- Knowledge of AI security, responsible AI, model governance, and enterprise compliance.
- Experience leading AI modernization / legacy modernization initiatives.

Leadership Expectations

- Provide technical leadership for AI/GenAI engineering teams.
- Define architecture, technology standards, development patterns, and reusable frameworks.
- Review and guide AI solution designs and production implementations.
- Mentor engineers and conduct technical knowledge-sharing sessions.
- Work directly with senior stakeholders to translate business requirements into scalable AI solutions.
- Drive PoC-to-production conversion and ensure enterprise-grade quality.
- Contribute to AI capability building, innovation, and technical roadmap.

📌 AI Engineer (Hyderabad)
🏢 Zettamine Labs
📍 Hyderabad