Job Overview
Who's the hiring manager?
Sign up to PitchMeAI to discover the hiring manager's details for this job. We will also write them an intro email for you.
Job Description
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
How to Get Hired at Cognizant
- 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.
Frequently Asked Questions
Find answers to common questions about this job opportunity
Explore similar opportunities that match your background