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Salary
≈ $20k – $50k per year (Estimated)
Location
Hybrid (Gurgaon, India)
Seniority
Middle · 4+ years exp
Employment
Full-Time

Confirmed on the employer's own hiring board on Oct 11, 2026. First seen by Alion on Sep 28, 2026. Cognizant scores B on the Alion truth index.

Overview
Company
Impact
Profile match
Cognizant is an American information technology services and consulting company founded in 1994 as an in-house technology unit of Dun and Bradstreet in Chennai, India, and headquartered in Teaneck, New Jersey. It builds, integrates and operates software and infrastructure for large enterprises, with particularly deep positions in healthcare, financial services, insurance and life sciences, delivered by a global workforce of more than three hundred thousand people concentrated in India. Listed on Nasdaq, the company competes with the large Indian and global systems integrators and has reoriented its offerings around cloud migration, data platforms and AI-assisted engineering.

About Cognizant Consulting

Cognizant Consulting is more than Cognizant's consulting practice, we're a global community of 5,000+ experts dedicated to helping clients reimagine their business. Blending our deep industry and technology advisory capability, we create innovative business solutions for Fortune 500 clients. And now, we're looking for our next colleague who'll join us in shaping the future of business. Could it be you?

About the role

As a Senior AI Engineer, you will make an impact by designing, building and operating production-grade AI and machine learning solutions across generative AI, RAG, agentic AI, data science, data engineering and cloud-native application development. You will be a valued member of the Tech Consulting Group team and work collaboratively with client and business stakeholders, and clients.

In this role, you will

  • Design, develop, deploy and support production-grade AI and machine learning solutions across the complete engineering lifecycle, including requirements analysis, design, development, testing, deployment, monitoring and continuous improvement.
  • 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 patterns such as single-agent, multi-agent, supervisor-worker, human-in-the-loop and event-driven architectures, implemented with frameworks such as LangGraph, LangChain, Semantic Kernel, AutoGen, CrewAI or LlamaIndex.
  • Develop and evaluate machine learning and deep learning models, including NLP use cases, and build scalable data pipelines across relational, NoSQL, analytical, search, vector and graph data platforms.
  • Deploy and operate AI workloads on AWS, Microsoft Azure or Google Cloud using established MLOps, LLMOps and CI/CD practices, and monitor, troubleshoot and optimize solutions for quality, performance, scalability, security, governance and cost.

Work model

At Cognizant, we strive to provide flexibility wherever possible. Based on this role's business requirements, this is a hybrid position requiring three days a week in a client or Cognizant office in Chennai, Bengaluru, Hyderabad, NCR, Pune, Kolkata or another Cognizant office location in India. Regardless of your working arrangement, we are here to support a healthy work-life balance through our various wellbeing programs.

The working arrangements for this role are accurate as of the date of posting. This may change based on the project you're engaged in, as well as business and client requirements. Rest assured; we will always be clear about role expectations.

What you must have to be considered

  • At least four years of hands-on experience delivering production-grade AI and machine learning solutions.
  • Practical expertise in generative AI, RAG, agentic AI, machine learning, data science and data engineering.
  • Experience building AI-enabled APIs, microservices and application components and integrating AI capabilities with enterprise data and applications.
  • Hands-on experience deploying and operating AI workloads on AWS, Microsoft Azure or Google Cloud using software engineering, MLOps, LLMOps and CI/CD practices.
  • A background from a premium engineering college.

These will help you succeed

  • Experience designing GraphRAG and knowledge graph-based retrieval architectures.
  • Familiarity with agentic frameworks such as LangGraph, LangChain, Semantic Kernel, AutoGen, CrewAI or LlamaIndex.
  • Experience developing AI-driven workflow automation by integrating agents with enterprise applications, APIs, tools, business rules and approval processes.
  • Strong stakeholder engagement skills, including presenting architectural trade-offs and driving consensus on technical direction.
  • Ability to produce maintainable code and technical documentation and contribute to engineering reviews and production readiness.
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