Hiring for Returnship
Only for Female Candidates.
JD.
Experience - 5-10years
Level - TM/SDM
Location - Pan India
NP - Immediate
GenAI or GenAI Architect
Build GenAI applications using Python for tasks like chatbots, summarization and intelligent automation.
• Develop and fine tune LLMs and ML models for classification, prediction, and decision support.
• Design solutions using embeddings, vector search, and retrieval augmented generation (RAG).
• Deploy models using Azure Machine Learning and Azure OpenAI scale with Azure Functions and Cognitive Services.
• Integrate models with AWS services like SageMaker, Lambda, Bedrock and data platforms like Snowflake.
• Integrate AI systems with APIs, enterprise data platforms and business workflows.
Strong Python development with experience in GenAI frameworks like LangChain, Hugging Face, OpenAI.
- A. LLMs and hyperparameters (Azure / AWS / GCP / Open Source)
- B. Embedding models and vector database knowledge
- C. Prompting Techniques (Zero shot, few shot, chain of thought)
- D. Frameworks: Langchain, Pydantic
- E. RAG, Problem solving skills on where to apply RAG / Other Gen AI techniques.
- B. Frameworks like Pandas, Fast API, Numpy
Preferred Skills
• Solid foundation in ML algorithms, training pipelines and evaluation techniques.
• Familiarity with prompt engineering, tokenization and model optimization.
• Hands-on with Azure cloud tools for model lifecycle, deployment and serverless execution.
• Ability to connect models to data sources, automation tools and orchestration platforms.
System Design: Develop and design the architecture for AI systems, ensuring they integrate seamlessly with business operations.
2. Technology Selection: Choose appropriate technologies and tools for building and deploying generative AI solutions.
3. Scalability: Ensure the AI systems are scalable and can handle increasing workloads efficiently.
4. Model Management: Oversee the lifecycle of generative AI models, including development, deployment, and maintenance.
5. Prompt Engineering: Design and refine prompts used in natural language processing models to optimize performance.
6. Data Integration: Integrate data from various sources to support AI model training and inference.
7. Performance Optimization: Continuously monitor and optimize the performance of AI models and systems.
8. Security and Compliance: Ensure AI systems adhere to security protocols and compliance standards.
9. Collaboration: Work closely with data scientists, ML engineers, and other stakeholders to align AI solutions with business goals.
10. Innovation: Stay updated with the latest advancements in AI and incorporate innovative solutions into the architecture.
关于高知特 (Cognizant)
高知特(Cognizant)（纳斯达克代码：CTSH）作为一家AI Builder和相关技术服务提供商，致力于通过打造全栈AI解决方案，帮助企业将人工智能投资转化为实际价值。公司凭借深厚的行业经验、流程优化和工程技术专长，将企业独特的业务场景融入科技系统，赋能组织释放人才潜能，推动切实成果，并帮助全球企业在瞬息万变的环境中保持领先。如需了解更多详情，敬请访问 cognizant.ai 或关注@cognizant。
补充雇佣信息
薪酬信息截至本职位发布之日为准。Cognizant 保留在适用法律允许的范围内随时修改该信息的权利。
申请人可能需要通过现场面试或视频会议的方式参加面试。此外，候选人在每次面试时可能需要出示其当前所在州或政府签发的有效身份证件。
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