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Senior AI Engineer Python & Generative AI

- Job Title: Senior AI Engineer
- Department: AI & ML
- Experience: 35 years
- Location: SNP Cloud Technologies, 12th Floor, Western Aqua, Cross Street 1, Whitefields, HITEC City, Hyderabad, Telangana 500081
- Job Type: Full-time, Regular, Work from Office
- Reports To: Technical Lead, AI

Summary We are looking for a hands-on Senior AI Engineer with strong Python skills and practical experience building AI and Generative AI applications. You will design, build, and ship production-grade AI features — from RAG pipelines and LLM-powered services to ML models and agentic workflows — working closely with the Technical Lead and cross-functional teams. This is a core individual-contributor role for an engineer who writes clean code, owns features end to end, and wants to grow toward technical leadership

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Responsibilities

Python & Backend Engineering:

- Design, develop, and maintain Python services, REST APIs, and microservices (FastAPI / Flask) that expose AI capabilities.
- Write clean, modular, well-tested code following Python best practices (typing, linting, unit/integration tests).
- Build data processing and ingestion pipelines (document parsing, chunking, embedding, ETL) that feed AI/ML workloads.
- Containerise services with Docker and contribute to CI/CD pipelines for automated testing and deployment.
- Debug, profile, and optimise services for latency, reliability, and cost.

Generative AI & LLM Applications:

- Build RAG (Retrieval-Augmented Generation) pipelines end to end — ingestion, chunking strategy, embeddings, vector search, re-ranking, and grounded response generation.
- Develop LLM-powered applications using Azure OpenAI and other model providers, with effective prompt engineering and structured outputs.
- Implement agentic workflows — tool/function calling,



planning agents, and multi-agent orchestration — using frameworks such as LangChain, LangGraph, Semantic Kernel, or AutoGen.
- Build or integrate MCP (Model Context Protocol) servers and tools to connect agents with enterprise systems and data.
- Work with vector databases (Azure AI Search, Pinecone, Qdrant, Chroma, FAISS, pgvector, etc.).
- Set up evaluation for LLM outputs (relevance, groundedness, hallucination checks) and apply guardrails, content safety, and PII handling.

Machine Learning & Azure AI:

- Use Azure AI services (Azure OpenAI, AI Search, Document Intelligence, Vision, Language, Speech, Azure ML) to build intelligent applications.
- Train, fine-tune, and evaluate ML/DL models using Scikit-learn, PyTorch, or TensorFlow where the use case requires it.
- Track experiments and manage models with MLflow or Azure ML; support model deployment and monitoring in production.

Collaboration & Ownership:

- Take ownership of features from requirement to production, including design, estimation, development, testing, and deployment.
- Work with the Technical Lead, product, and business teams to turn requirements into technical solutions.
- Take part in code reviews and mentor junior engineers on coding standards and AI engineering practices.
- Write transparent technical documentation and present solutions or POCs to stakeholders.
- Keep up with advances in LLMs, agent frameworks, and MLOps,



and propose improvements to the current stack.

Qualifications:

Required:

- Bachelor’s or Master’s degree in Computer Science, AI, Data Science, or a related field (or equivalent experience).
- 3–5 years of professional software engineering experience, with at least 1.5–2 years hands-on in AI/ML or Generative AI projects.

Solid expertise in:

- Python (FastAPI / Flask, asyncio, OOP, Pydantic) and REST API development.
- LLM application development — prompt engineering, function/tool calling, and RAG pipelines.
- At least one LLM/agent framework (LangChain, LangGraph, LlamaIndex, Semantic Kernel, or similar).
- Vector databases and embedding models.
- Data handling with Pandas and NumPy.
- Hands-on experience with at least one ML framework (Scikit-learn, PyTorch, or TensorFlow).
- Git, Docker, and working within Agile and CI/CD processes.
- Good communication and problem-solving skills, with the ability to explain technical decisions clearly.

Preferred:

- Experience with Microsoft Azure — Azure OpenAI, Azure AI Search, Azure ML, Azure Functions / App Service / AKS.
- At least one GenAI or ML solution deployed to production (not just POCs).
- Exposure to agentic architectures — tool-using agents, planning agents, or multi-agent workflows.
- Familiarity with MCP (Model Context Protocol) — building MCP servers, exposing tools, or integrating agents with MCP.
- Experience with LLM evaluation and observability tools (RAGAS, DeepEval, Langfuse, LangSmith, Azure AI Foundry evaluations).
- Knowledge of MLOps tools such as MLflow, Kubeflow, or Azure ML pipelines.
- Exposure to fine-tuning techniques (LoRA / PEFT) or open-source LLMs (Llama, Mistral, etc.).
- Relevant certifications (e.g., Microsoft Azure AI Engineer Associate – AI-102).

📌 Senior Artificial Intelligence Engineer (Hyderabad)
🏢 SNP Cloud Technologies
📍 Hyderabad