**About the Role:** The ideal candidate should have a solid background in **backend development, AI/ML orchestration, and data management** , with hands-on experience in **Generative AI and Agentic AI frameworks** . They will be responsible for **building REST APIs** , managing **data pipelines** , and implementing **AI/ML solutions** such as **retrieval-augmented generation (RAG)** , **intent detection models** , and **autonomous AI agents** to deliver intelligent, production-ready solutions. **Key Responsibilities:** · **Backend Development** : Design, develop, and maintain REST APIs using Python to integrate AI/ML services. · **Agentic AI Development** : Design and orchestrate **AI agents** capable of reasoning, planning, and executing multi-step tasks by integrating LLMs with APIs, tools, and data sources. · **AI/ML Orchestration** : Implement and manage machine learning models, large language models (LLMs), Agentic AI workflows and AI orchestration using Python. · **Generative AI Solutions** : Using Generative AI models for tasks like text generation, summarization, conversational AI, and content creation. · **Data Management** : Work with structured databases (SQL), graph databases (e.g., CosmosDB), and unstructured data stores (e.g., Elasticsearch). · **RAG Implementation** : Build retrieval-augmented generation (RAG) pipelines leveraging Azure AI Search, AWS OpenSearch, or other vector databases for contextual responses. · **Data Pipelines** : Design and manage robust data ingestion and transformation pipelines to feed AI models. · **Intent Detection & NLU** : Develop or integrate intent detection models and natural language understanding (NLU) solutions to enhance conversational AI. · **Prompt Engineering & Optimization** : Create and optimize prompts for LLMs to improve response quality and reduce latency. · **AI Integration** : Collaborate with frontend and product teams to embed Gen AI features into enterprise applications. **Required Skills:** · **Backend Development** : Proficient in Python for building and maintaining scalable REST APIs, familiarity with integrating AI services. · **AI/ML Orchestration** : Strong expertise in Python with a focus on machine learning, large language models (LLMs), AI orchestration. · **Agentic AI Expertise:** Experience in building **autonomous AI agents** using frameworks like OpenAI Functions, or custom orchestration solutions to handle tool use and multi-step reasoning. · **Generative AI Expertise** : Generative AI models (text generation, summarization, conversational AI) and applying prompt engineering techniques. · **Data Management** : Solid understanding of structured (SQL), graph (CosmosDB), and unstructured (Elasticsearch) databases; ability to design efficient data access patterns for AI workloads. · **RAG Implementation** : Proven experience implementing retrieval-augmented generation using Azure AI Search, AWS OpenSearch, or other vector databases. · **Data Pipelines** : Hands-on experience building and managing data ingestion and transformation pipelines using Databricks, Azure Data Factory, or equivalent tools. · **Intent Detection & NLU** : Skilled in developing or deploying intent detection models and natural language understanding (NLU) components for conversational AI applications. **Preferred Skills:** · Familiarity with cloud platforms such as Azure and AWS. · Knowledge of additional AI/ML frameworks and tools. · Knowledge of Agentic AI · Experience with DevOps practices and CI/CD pipelines. Cognizant is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to sex, gender identity, sexual orientation, race, color, religion, national origin, disability, protected Veteran status, age, or any other characteristic protected by law.