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Job Title –AI Engineer / Generative AI Engineer
Base Location – Hyderabad
Duration – Full time
** Immediately to 15 days**
Job description:
We are looking for a skilled AI Engineer with 4–6 years of experience to design, develop, and deploy AI-driven solutions across the organization. This role focuses on building and integrating Generative AI applications, supporting Responsible AI practices, and embedding AI into the Software Development Life Cycle (SDLC).
The ideal candidate will have hands-on experience with Large Language Models (LLMs) such as OpenAI (ChatGPT) and Anthropic (Claude), along with exposure to agent-based systems and modern AI development practices.
Key Responsibilities:
AI Development & Implementation
LLM & Generative AI Solutions
AI Integration into SDLC
Agentic AI & Automation (Exposure)
AI Governance, Security & Compliance (Support Role)
Collaboration & Delivery
Required Technical Skills
AI / ML & LLMs
Programming & Development
Architecture & Integration
DevOps & MLOps
Data Security & Compliance
Preferred Qualifications
Soft Skills
Education:
Job ID: 146494017
Skills:
data pipeline, API design, Tensorflow, Pytorch, Docker, Python, AWS, Gcp, Azure, Kubernetes, CI CD for AI, Pinecone, backend systems, Mistral, Distributed microservices, model monitoring, LangChain, LLaMA, LLMs, Anthropic, FAISS, xVector DBs, RAG, drift detection, Milvus, OpenAI, Weaviate
Skills:
Adf, Agentic AI, algorithms for generative models, generative models, GenAI systems
Skills:
Pycharm, Bdd, Fiddler, Jira, Soapui, Jenkins, Git, Jmeter, Tdd, Gherkin, Postman, Selenium with Python, VS Code, LLM testing, Agents testing, Pytest framework
Skills:
Machine Learning, Artificial Intelligence, Google Cloud, Tensorflow, Deep Learning, Docker, Pytorch, Keras, Python, AWS, GANs, LLMs, cloud platforms, Generative Models, Transformers, Generative AI models
Skills:
Sql, Django, REST, Flask, Swagger, Postgres, Redis, FastAPI, Kubernetes, Python, Azure, Restful Apis, attention tokens, context window, AIML, Core AI, LLM behavior, data processing pipelines, MCP, RAG, automation testing frameworks, operational monitoring, Llm, Transformers, OpenAPI, model evaluation procedures, MCP Model Context Protocol, observability, FastMCP, Docket
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