AI Architect
Cognizant · Chennai, Tamil Nadu, India
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- On site
- Full-time
- $150,000 / year
- Chennai, Tamil Nadu, India
Job highlights
- Design and deploy complex autonomous AI agent systems.
- Architect AI/ML solutions on Azure, AWS, or GCP.
- Develop dynamic context with memory and retrieval strategies.
- Manage full ML/AI lifecycle from data to deployment.
- Lead technical architecture and collaborate with stakeholders.
About the role
AI Agentic Architect/Lead
The Architect/Lead is responsible for the end-to-end vision, design, and successful production deployment of complex, autonomous AI systems (Agents). Hands-on expertise in architecting and deploying AI/ML solutions on a leading cloud platform Azure/AWS/GCP. Demonstrated expertise in Python and modern ML/AI frameworks, with the ability to design, implement, and optimize complex agentic workflows.
System Design & Architecture
Lead the design and development of agentic systems using GenAI and Machine Learning. This involves selecting the right frameworks (like LangChain, LlamaIndex, or proprietary solutions) and architectural patterns. Engineer dynamic context using memory modules, prompt templates, and retrieval strategies. Define and enforce guardrails and context governance across agent interactions and LLM outputs. Prioritize security by implementing secure architecture patterns.
Full-Stack ML/AI Engineering Expertise
Own the full lifecycle: data sourcing, model development, orchestration, deployment, and LLMOps. Rapidly prototype solutions to validate technical feasibility and then successful Minimum Viable Products (MVPs) into robust, scalable enterprise applications that demonstrably meet core KPIs. Proven hands-on experience with agentic AI frameworks such as LangChain, LangGraph, CrewAI, or equivalent, including designing multi-agent workflows and tool-augmented reasoning systems. Determine when and how to apply fine-tuning or prompt engineering to optimize model performance. Expertise in applying advanced model selection, feature engineering, and evaluation techniques. Establish monitoring strategies utilizing cloud-native tools like Azure Monitor and Application Insights.
Institute MLOps/LLMOps practices for tracking model iterations, deployment gates, rapid restoration, and actively monitoring drift detection.
Design and automate Continuous Integration and Continuous Delivery (CI/CD) pipelines, leveraging tools like Azure DevOps, GitHub Actions, or similar systems.
Technical Leadership
Serve as the authority on critical architectural choices, trade-offs, and technology stack selection. Work closely with Product Owners to define requirements, Data Scientists, Business Stakeholders acting as the primary technical interface.
Key skills/competency
- AI Architect
- Agentic Systems
- GenAI
- Machine Learning
- Python
- Cloud Platforms (Azure/AWS/GCP)
- MLOps/LLMOps
- LangChain
- System Design
- Technical Leadership
Skills & topics
- AI Architect
- Agentic Systems
- GenAI
- Machine Learning
- Python
- Cloud Platforms
- Azure
- AWS
- GCP
- MLOps
- LLMOps
- LangChain
- System Design
- Technical Leadership
How to get hired
- Tailor your resume: Highlight AI Architect Lead experience, Python, ML frameworks, and cloud platforms.
- Showcase agentic AI skills: Emphasize experience with LangChain, LangGraph, or CrewAI and multi-agent workflows.
- Quantify achievements: Provide metrics on successful production deployments and KPI attainment.
- Prepare for technical interviews: Be ready to discuss system design, MLOps, and LLMOps best practices.
- Network with hiring managers: Directly connect with the hiring manager to express interest.
Technical preparation
Behavioral questions
Frequently asked questions
- What are the key responsibilities of an AI Architect Lead at Cognizant?
- The AI Architect Lead at Cognizant is responsible for the end-to-end vision, design, and production deployment of complex, autonomous AI systems (Agents). This includes architecting AI/ML solutions on cloud platforms, developing agentic workflows, and leading technical design and implementation efforts.
- What cloud platforms are preferred for this AI Architect Lead role at Cognizant?
- This AI Architect Lead role requires hands-on expertise in architecting and deploying AI/ML solutions on leading cloud platforms such as Azure, AWS, or GCP.
- What programming languages and AI frameworks are essential for the Cognizant AI Architect Lead position?
- Proficiency in Python and modern ML/AI frameworks is essential. Experience with agentic AI frameworks like LangChain, LangGraph, or CrewAI is highly valued for designing multi-agent workflows and tool-augmented reasoning systems.
- Does the AI Architect Lead role at Cognizant involve MLOps/LLMOps practices?
- Yes, the role involves instituting MLOps/LLMOps practices for tracking model iterations, deployment gates, rapid restoration, and monitoring drift detection, ensuring efficient and reliable AI system management.
- How does Cognizant ensure security in its AI systems for this role?
- Security is prioritized by implementing secure architecture patterns within the agentic systems, including defining and enforcing guardrails and context governance across agent interactions and LLM outputs.
- What is the expected technical leadership contribution from an AI Architect Lead at Cognizant?
- The AI Architect Lead will serve as the authority on critical architectural choices, trade-offs, and technology stack selection, acting as the primary technical interface for Product Owners, Data Scientists, and Business Stakeholders.
- How can I apply for the AI Architect Lead position at Cognizant?
- To apply for the AI Architect Lead position at Cognizant, please send your resume to jwalesh.b@cognizant.com.