AI Engineer JD:
Location - PAN India
Experience Range - 3 to 9 Years
Role Overview
We are seeking a Senior AI Engineer with at least four years of hands-on experience delivering production-grade AI and machine learning solutions. The role requires expertise in generative AI, RAG, agentic AI, machine learning, data science, data engineering, and cloud-native application development.
The engineer will own the delivery lifecycle, including requirements analysis, technical design, development, testing, deployment, monitoring, debugging, and continuous improvement. The role involves integrating AI capabilities with enterprise data and applications while ensuring security, scalability, performance, and maintainability.
Key Responsibilities
· Design, develop, deploy, and support production-grade AI and machine learning solutions throughout the complete engineering lifecycle.
· Design and implement production-grade RAG and GraphRAG architectures, selecting vector, hybrid, or knowledge graph-based retrieval patterns based on data, use-case, scalability, and response-quality requirements.
· Design and develop agentic AI solutions using appropriate patterns such as single-agent, multi-agent, supervisor-worker, human-in-the-loop, and event-driven architectures.
· Implement agentic workflows using frameworks such as LangGraph, LangChain, Semantic Kernel, AutoGen, CrewAI, LlamaIndex, or equivalent technologies.
· Develop AI-driven workflow automation by integrating agents with enterprise applications, APIs, tools, business rules, and approval processes.
· Develop and evaluate machine learning and deep learning models, including NLP use cases, using sound data science, experimentation, validation, and performance measurement practices.
· Design data models and build scalable data pipelines for high-volume, diverse datasets across relational, NoSQL, analytical, search, vector, and graph data platforms.
· Build AI-enabled APIs, microservices, and application components and integrate them with enterprise and user-facing systems.
· Deploy and operate AI workloads on AWS, Microsoft Azure, or Google Cloud using established software engineering, MLOps, LLMOps, and CI/CD practices.
· Monitor, troubleshoot, and optimize production AI solutions for quality, performance, scalability, security, governance, and cost.
· Produce maintainable code and technical documentation while contributing to solution design, engineering reviews, production readiness, and stakeholder discussions.
· Engage directly with client and business stakeholders to shape solution design, present architectural trade-offs, and drive consensus on technical direction.
Required Qualifications
- Bachelor’s or master’s degree in Computer Science, Artificial Intelligence, Data Science, Engineering, Mathematics, Statistics, or a related quantitative discipline.
- At least four years of hands-on experience, with demonstrable contributions to three or more production-grade AI projects across design, development, deployment, and support.
- Strong hands-on skills in Python, machine learning, deep learning, NLP, and data engineering, including data preparation, modeling, pipeline development, model evaluation, and production-grade coding.
- Hands-on data engineering experience building scalable pipelines and data models for high-volume, diverse datasets, including schema design and SQL, NoSQL, analytical, search, or vector data stores.
- Experience developing REST APIs, microservices, or back-end services and integrating AI capabilities with enterprise or user-facing applications.
- Hands-on experience deploying solutions on at least one major cloud platform: AWS, Microsoft Azure, or Google Cloud.
- Experience with Git, CI/CD, automated testing, and containerized or serverless deployments.
- Experience monitoring, debugging, and securing production AI solutions using appropriate observability, access control, data privacy, and responsible AI practices.
- Excellent verbal and written communication skills, with demonstrated ability to engage with clients/stakeholders
Preferred Qualifications
- Relevant professional certifications in AWS, Microsoft Azure, or Google Cloud.
- Experience working in a mature product engineering, technology consulting, enterprise data, or AI practice with structured engineering and production-support processes.
- Experience with enterprise AI/ML services on at least one major cloud platform; multi-cloud exposure is an advantage.
- Experience with modern data platforms, distributed and streaming data processing, workflow orchestration, and messaging systems.
- Knowledge of infrastructure as code, Kubernetes, cloud security, observability, and performance engineering.
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。
Cognizant 是一家提供平等就业机会的雇主。在招聘过程中，您的申请和候选资格不会因种族、肤色、性别、宗教、信仰、性取向、性别认同、国籍、残疾、遗传信息、怀孕、退伍军人身份或任何其他受联邦、州或地方法律保护的特征而受到影响。
