Cognizant
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Unknown · São Paulo, Brazil
Hiring: Engineering
What employees say
+ Initiative the works to develop technical knowledge
− There is no time consumption
More reviews on the company profile.
Interview experience · Jr.Software Engineer
1)2Technical round (Based on Technical Skill ,Two Coding based Question,SQL) 2)Hr discussion (if selected ) Cognizant helps companies modernize technology, reimagine processes and transform experiences so they stay ahe
Average difficulty · India · 3 reports
More interview insightsJob description
Overview
About Cognizant Consulting
Responsibilities
- 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.
- 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.
Qualifications
- 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.
- Familiarity with agentic frameworks such as LangGraph, LangChain, Semantic Kernel, AutoGen, CrewAI or LlamaIndex.
- 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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Job application FAQ
Last updated 1 October 2026
- How do I apply for AI Engineer at Cognizant?
- Open this job on Feedback AI and sign up free (or sign in). You can apply from the job detail page; match scores and skill gaps appear when your profile is complete. Cognizant may attach structured assessments to interview rounds after you apply.
- Does Feedback AI show a match score for this AI Engineer role?
- Yes after you add a resume or skills. Match score ranks this role against your profile — skills met, gaps, level, and location — so you prioritise applications where fit is strongest.
- Is AI Engineer remote or on-site in Gurugram, Haryana?
- This listing is marked hybrid with location Gurugram, Haryana. Confirm details on the job description before applying.
- What skills matter for this AI Engineer role at Cognizant?
- This is a mid-level AI Engineer role. Key skills include Hybrid. Feedback AI highlights matched vs missing skills on your profile after signup.