This role is no longer listed.IQVIA took the posting down on 4 Nov, so applying now won't reach anyone. It stays here for your saved list and any links you shared.
AI Architect - GenAI & Agentic Systems
IQVIA (company site, opens in a new tab)KochiOn-siteDirect career pageEst. 30–50 LPA
Posted 20h ago
Reach people at IQVIA
People at this company you can reach
Log in to see who works here
Create a free account or log in to see the people at IQVIA you could write to:
- Recruiters & HR
- People in this function
- Work addresses
Your match
Against your primary resume
Log in to see your match score
Create a free account or log in to unlock your CV match score across:
- Role fit
- Experience
- Industry relevance
Protocol Intelligence
How competitive this role is
Competition
Background fit
Strictness
Log in to see why each signal reads the way it does.
Job description
Structured overview of role & requirements
About This Role
- Design, build, and deploy end-to-end automation and Generative AI solutions on cloud-native platforms including production systems with post-deployment monitoring.
- Develop agentic systems involving LLMs and Generative AI models, multi-agent orchestration using frameworks such as LangChain, LangGraph, and implement tool orchestration with safeguards like human approval and sandboxing.
- Lead deployment via scalable CI/CD pipelines on Azure and/or AWS, handle monitoring of performance and cost metrics, and partner with stakeholders to prototype and drive adoption.
Minimum Requirements
- Strong proficiency in Python and hands-on development experience.
- Experience with Azure and/or AWS cloud platforms and CI/CD for safe rollout of services.
- Experience with Generative AI, LLM-based systems, RAG pipelines, and frameworks like LangChain or LangGraph.
- Work Experience Required: Not explicitly mentioned in the JD.
Ideal Candidate Profile
- Experienced in architecting and operating agentic AI systems with monitoring and quality metrics focus.
- Hands-on with advanced GenAI capabilities including multi-agent orchestration and RAG architectures.
- Comfortable working independently to deliver production-ready AI/automation solutions with strong stakeholder collaboration.