AI Engineer
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Job Description
AI Engineer – Python & Generative AI
Position: AI Engineer
Experience: 3 – 6 Years
Location: Chennai
Work Mode: Work From Office
Employment Type: Full-Time
Function: Artificial Intelligence / Engineering
About the Role
We are looking for a skilled AI Engineer with strong hands-on experience in Python and Generative AI technologies to design, build, and deploy intelligent AI-driven solutions. The ideal candidate will have a solid foundation in machine learning concepts along with practical exposure to LLMs, RAG pipelines, and AI application development.
Key Responsibilities
- Design, develop, and deploy AI/ML models and Generative AI applications using Python.
- Build and optimize RAG (Retrieval-Augmented Generation) pipelines integrating LLMs with vector databases.
- Fine-tune and prompt-engineer LLMs (OpenAI, Mistral, Gemini, LLaMA, etc.) for specific business use cases.
- Develop AI agents/chatbots and integrate them with enterprise applications and APIs.
- Work with frameworks such as LangChain, LlamaIndex, and Hugging Face Transformers for GenAI solution development.
- Collaborate with cross-functional teams (Product, Data Engineering, DevOps) to build scalable AI solutions.
- Implement and manage vector databases (Pinecone, Chroma, FAISS, Weaviate, etc.).
- Conduct model evaluation, testing, and performance optimization for accuracy and latency.
- Stay updated with the latest advancements in AI/ML and Generative AI technologies and recommend adoption where relevant.
- Ensure best practices in code quality, version control, and documentation.
Required Skills & Qualifications
- 5+ years of overall experience in AI/ML engineering, with strong proficiency in Python.
- Hands-on experience with Generative AI / LLMs (OpenAI GPT, Google Gemini, Anthropic Claude, Mistral, LLaMA, etc.).
- Practical experience with RAG architecture, prompt engineering, and LLM fine-tuning.
- Familiarity with AI/ML frameworks: LangChain, LlamaIndex, Hugging Face, TensorFlow/PyTorch.
- Experience working with Vector Databases (Pinecone, Chroma, FAISS, Weaviate, etc.).
- Strong understanding of NLP, Machine Learning, and Deep Learning concepts.
- Experience with cloud platforms (AWS, Azure, or GCP) for AI model deployment.
- Familiarity with REST APIs, containerization (Docker), and basic MLOps practices.
- Good understanding of SQL/NoSQL databases.
- Strong analytical, problem-solving, and communication skills.
Good to Have
- Experience with AI Agent frameworks (Agent SDKs, AutoGen, CrewAI, etc.).
- Exposure to Kubernetes and CI/CD pipelines.
- Prior experience in building chatbots, virtual assistants, or automation solutions.
- Knowledge of AI governance, responsible AI, and model evaluation frameworks.
Education
- Bachelor's/Master's degree in Computer Science, Information Technology, AI/ML, or a related field.
Work Mode
Work From Office – Chennai
Interested candidates kindly share your resume to [Confidential Information]
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Key Skills
About Company
Skills:
Cloud Services, C++, Sql, Tensorflow, Pytorch, MLops, Azure, Python, AWS, data pipelines, scikit-learn, gradient boosting methods
Skills:
Git, system integration, Docker, Linux, Microsoft Azure, Rest Apis, Python, embeddings, LLMs, Microsoft Foundry, vector databases, CI CD, Azure OpenAI, Semantic Kernel, LangGraph, knowledge retrieval, RAG, on-premise deployment, Microsoft Agent Framework, SQL databases, semantic search
Skills:
Retrieval-Augmented Generation (RAG) architectures, Large Language Models (LLMs), Agentic AI frameworks and multi-step reasoning workflows, Prompt engineering and prompt optimization techniques
Skills:
Large Language Models (LLMs), Tensorflow, Pytorch, Docker, Python, AWS, MLops, Gcp, Rest Apis, Kubernetes, embeddings, Hugging Face Transformers, vector databases, Pinecone, Azure AI Foundry, Azure AI Search, semantic search, RAG architectures, LangChain, Generative AI, LLMOps, CI/CD pipelines, FAISS, Milvus, Weaviate, LlamaIndex
Skills:
Cloud Engineering, Microservices, Tensorflow, Gcp, Pytorch, Terraform, XGBoost, Restful Apis, Python, LangChain, CI CD Pipelines, Generative AI, Tekton, scikit-learn, AI ML Development, MLOps Governance, AutoGen, LlamaIndex