Job Description & Summary: A career within…. 

Responsibilities: 

• Strong understanding of Generative AI concepts including Large Language Models (LLMs), prompt engineering, fine-tuning, and model evaluation. 

• Proficiency in Python/PySpark for AI development, data preprocessing, and scripting. 

• Hands-on experience in designing and implementing GenAI applications such as chatbots, document summarization tools, code assistants, or knowledge search solutions. 

• Deep understanding of embedding generation, vector databases (e.g., Amazon OpenSearch, Pinecone, FAISS), and retrieval-augmented generation (RAG) pipelines. 

• Proficiency in Python and frameworks such as LangChain, Transformers, and PyTorch/TensorFlow. 

• Experience with LLM APIs (e.g., OpenAI, Anthropic, Claude, Llama, etc.) and vector databases (e.g., OpenSearch, Pinecone, FAISS). 

• Ability to design and deploy scalable AI pipelines leveraging cloud platforms — preferably AWS, but Azure experience is also acceptable. 

• Understanding of data security, access control, and cost optimization in a cloud environment. 

• Strong knowledge of API development, microservices, and integration of GenAI systems into enterprise applications. 

• Strong understanding and hands-on experience with AWS AI and ML services, including Bedrock, SageMaker, Lambda, Step Functions, API Gateway, and CloudWatch. 

• Familiarity with cloud-native AI services such as AWS Bedrock, SageMaker, or Azure OpenAI. 

Mandatory skill sets: 

GEN AI, Python/Pyspark 

Preferred skill sets: 

• Proficiency in developing and integrating RESTful APIs 

• Understanding of version control systems, such as Git. 

• Experience in MLOps/DevOps practices for model deployment and monitoring. 

• Exposure to containerization (Docker, Kubernetes) for AI workloads. 

• Knowledge of AI governance, ethical AI, and responsible AI frameworks. 

• Strong analytical and problem-solving abilities, with a focus on performance optimization. 

• Experience working in Agile delivery environments and collaborating with cross-functional teams. 

• Experience integrating GenAI systems with business intelligence or automation solutions (e.g., chatbots, document summarization, code generation). 

• Proven experience in designing and implementing Extract, Transform, Load (ETL) processes 

• Knowledge of data governance, ethical AI principles, and responsible AI practices. 

• Knowledge in AWS or Azure Data Engineering services 

Years of experience required: 

4 – 7 yrs 

Education qualification: 

MBA/MCA/Btech