What are the responsibilities and job description for the AI Engineer - NJ/ Dallas/ Atlanta position at Cognizant?
Job Description
""We are seeking a GenAI Engineer to design, build, and deploy generative AI solutions that support enterprise applications, automation, knowledge discovery, and intelligent user experiences. The ideal candidate will have hands-on experience working with large language models, prompt engineering, retrieval-augmented generation, model evaluation, and application integration. Experience with Azure DevOps is helpful for supporting deployments, CI/CD workflows, and collaboration with engineering teams, though this role is not primarily DevOps-focused.
Key Responsibilities
""We are seeking a GenAI Engineer to design, build, and deploy generative AI solutions that support enterprise applications, automation, knowledge discovery, and intelligent user experiences. The ideal candidate will have hands-on experience working with large language models, prompt engineering, retrieval-augmented generation, model evaluation, and application integration. Experience with Azure DevOps is helpful for supporting deployments, CI/CD workflows, and collaboration with engineering teams, though this role is not primarily DevOps-focused.
Key Responsibilities
- Design, develop, and integrate GenAI-powered applications using large language models and related AI services
- Build solutions involving prompt engineering, retrieval-augmented generation, embeddings, vector search, and AI agents
- Develop APIs, services, and application components that connect GenAI capabilities to business workflows
- Work with structured and unstructured data to support knowledge retrieval, summarization, classification, and content generation use cases
- Evaluate model performance, response quality, hallucination risk, and reliability across different scenarios
- Collaborate with product, data, engineering, and architecture teams to deliver scalable AI solutions
- Implement responsible AI practices including security, privacy, monitoring, explainability, and governance considerations
- Support deployment and release processes using tools such as Azure DevOps, Git, CI/CD pipelines, and cloud environments
- Create documentation, reusable patterns, and technical guidance for GenAI solution development
- Stay current with emerging GenAI frameworks, model capabilities, and best practices
- 3 years of software engineering, data engineering, machine learning, or AI application development experience
- Hands-on experience building applications with large language models
- Experience with prompt engineering, RAG architectures, embeddings, and vector databases
- Proficiency in Python and familiarity with APIs, microservices, or backend development
- Experience working with cloud-based AI services, preferably on Azure
- Understanding of model evaluation, testing, monitoring, and quality improvement techniques
- Familiarity with secure development practices and enterprise application integration
- Strong problem-solving, communication, and collaboration skills
- Experience with Azure OpenAI Service, Azure AI Search, Azure Machine Learning, or related Azure AI services
- Working knowledge of Azure DevOps, including repositories, boards, pipelines, and release workflows
- Experience with Agentic-LLM solutions using LangChain, LangGraph, or similar tools
- Experience with vector databases or search platforms such as Azure AI Search
- Familiarity with containerization, CI/CD, and deployment automation
- Experience supporting enterprise-scale AI solutions, chatbot platforms, knowledge assistants, or intelligent automation use case"""