As an AI Architect, You will design and build agentic AI systems for multiple Domains such as Healthcare/ Finance/ Retail etc.
You will combine GenAI, ML, and systems engineering to create AI agents that interact with machines, data streams, and enterprise systems.
Key Responsibilities
Design and implement agent-based AI workflows for different domains such as :
healthcare use cases (clinical assistants, triage agents, care pathway optimization, RCM automation)
Design agentic AI architectures for manufacturing workflows
Build multi-agent financial AI systems (analysis agents, compliance agents, advisory agents)
Implement RAG over financial documents, policies, contracts, and filings
Build LLM-powered systems (RAG, tool-calling agents, multi-agent orchestration)
Develop classical ML models (risk scoring, prediction, clustering, anomaly detection)
Implement HIPAA aware AI architectures with auditability and traceability
Implement GenAI systems using RAG over CRM, customer data, and content
Build full-stack applications (Python APIs, AI services, UI dashboards)
Integrate with EHRs, data lakes, and healthcare systems (FHIR/HL7 exposure preferred)
Integrate LLMs with sensor data, MES, ERP, and IoT platforms
Collaborate with SMEs to translate medical workflows into agent logic
Deploy, monitor, and optimize AI systems in Azure
Basic Qualifications: (what are the skills required to this job with minimum years of experience on each)
Strong experience in Python-based AI systems - 8+ Years
Hands-on experience with GenAI (LLMs, RAG, embeddings, prompt engineering) - 8+ Years
Experience with traditional ML (classification, regression, NLP, time-series)
Full-stack experience (API design + UI integration) - 5+ Years
Azure cloud experience (Azure ML, Azure OpenAI, Functions, AKS) - 5+ Years
Experience working in regulated or compliance-heavy domains
Comfortable working with subject-matter experts
Strong learning mindset and adaptability
Experience building production AI systems, not just prototypes
Ability to explain AI decisions to non-technical stakeholders
Interest in agentic AI and next-generation AI architectures
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