1 day ago
Gurgaon, IndiaMid Level / Senior
Responsibilities
- Design, develop, deploy, monitor, debug, optimize, and support production-grade AI and machine learning solutions.
- Design and implement RAG and GraphRAG architectures using vector, hybrid, and knowledge graph retrieval patterns.
- Develop agentic AI solutions and workflows using single-agent, multi-agent, supervisor-worker, human-in-the-loop, and event-driven patterns.
- Integrate AI agents with enterprise applications, APIs, tools, business rules, and approval processes.
- Develop and evaluate machine learning, deep learning, and NLP models using data science experimentation and validation practices.
- Design data models and build scalable pipelines for relational, NoSQL, analytical, search, vector, and graph data platforms.
- Build AI-enabled APIs, microservices, and application components for enterprise and user-facing systems.
- Deploy and operate AI workloads on major cloud platforms using software engineering, MLOps, LLMOps, and CI/CD practices.
- Contribute to solution design, engineering reviews, production readiness, technical documentation, and stakeholder discussions.
- Engage clients and business stakeholders to shape solutions, present architectural trade-offs, and drive technical consensus.
Requirements
- 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 and contributions to at least three production-grade AI projects across design, development, deployment, and support.
- Strong hands-on skills in Python, machine learning, deep learning, NLP, data preparation, modeling, pipeline development, model evaluation, and production coding.
- Experience building scalable data 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 deployment experience with AWS, Microsoft Azure, or Google Cloud.
- Experience with Git, automated testing, and containerized or serverless deployments.
- Experience monitoring, debugging, and securing production AI solutions using observability, access control, data privacy, and responsible AI practices.
- Excellent verbal and written communication skills with the ability to engage clients and stakeholders.
- Relevant professional certifications in AWS, Microsoft Azure, or Google Cloud are preferred.
- Experience with mature product engineering, technology consulting, enterprise data, or AI practices is preferred.
- Experience with modern data platforms, distributed and streaming data processing, workflow orchestration, messaging systems, infrastructure as code, Kubernetes, cloud security, observability, or performance engineering is preferred.
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About Cognizant
Cognizant is a public IT services and consulting firm that designs, builds, and runs enterprise technology, including digital engineering, cloud modernization, data/AI, and managed services. It sells consulting, systems integration, and outsourcing on multi-year engagements to large enterprises in healthcare, banking, retail, communications, and manufacturing. Founded in 1994 and headquartered in Teaneck, New Jersey, Cognizant is NASDAQ-listed (CTSH) and a Fortune 500 company.