Description

 Architect and deliver Agentic AI systems leveraging LLMs, autonomous agents, tool-using agents, and multi-agent orchestration frameworks. · Architect LLM powered systems · Design end-to-end ML and GenAI architectures including data pipelines, vector databases, RAG patterns, guardrails and AI Governance frameworks, and human-in-the-loop workflows. · Evaluate and integrate modern frameworks such as Langgraph, LangSmith LlamaIndex, Semantic Kernel, AutoGen or enterprise agent platforms. · Define architecture blueprints, solution patterns, reusable components, and best practices. Model Development & Engineering · Build, fine-tune, and optimize ML/Deep Learning/NLP/LLM-based models using Python and mainstream ML frameworks. · Lead experimentation, prototyping, and PoCs for autonomous agents, task decomposition, planning, and self-improving AI workflows. · Implement safety, governance, explainability, drift monitoring, and compliance controls. MLOps & GenAI Ops · Architect scalable CI/CD pipelines for AI/ML/Agentic solutions. · Deploy AI systems using Docker/Kubernetes, managed ML platforms Collaboration & Leadership · Partner with business teams to translate strategic objectives into AI-driven solutions. · Conduct architectural reviews and guide data scientists, ML engineers, and developers. · Communicate trade-offs, risks, and architectural decisions clearly to stakeholders. · Overall experience of 10-15 years · 8+ years in AI/ML Architecture · 3+ years of experience in Agentic AI/LLM based systems · Strong experience in Python, TensorFlow · Hands on in ML & LLMs · Cloud experience · Experience in Pharmacy, Healthcare Domain · Experience in designing and deploying AI agents on enterprise-grade runtimes (e.g., Amazon Bedrock AgentCore) including containerized execution, session management, and secure endpoint exposure. · Hands-on experience with agent runtime capabilities including state management, memory handling, asynchronous execution, and integration with external APIs/tools. · Knowledge of observability, monitoring, and debugging of agent executions including tracing, performance tuning, and failure recovery in production environments. · Experience with LLM-as-a-judge, human-in-the-loop evaluation, and rubric-based scoring models for qualitative assessment. Knowledge of hallucination detection, bias/safety evaluation, and grounding validation for enterprise-grade AI systems Generic Leadership Skills § Very good communication skills § Good Analytical skills § Ability to operate within a fast paced work environment a plus § Excellent communication (oral and written), facilitation, presentation, and organization skills required § Excellent organization skills preferred § Proven ability to manage multiple projects simultaneously required § Demonstrated problem solving and organization capabilities preferred Nice to have: · Understanding of pharmacy workflows · Familiarity with healthcare standards: FHIR, HL7, NCPDP, EHR/EMR systems. · Exposure to healthcare compliance: HIPAA, GxP, FDA regulatory frameworks. Role Descriptions: AIML  Agentic Architecture DesignArchitect and deliver Agentic AI systems leveraging LLMs| autonomous agents| tool using agents| and multi-agent orchestration frameworks.Architect LLM powered systems Design end-to-end ML and GenAI architectures including data pipelines| vector databases| RAG patterns| guardrails and AI Governance frameworks| and human-in-the-loop workflows.Evaluate and integrate modern frameworks such as Langgraph| LangSmith LlamaIndex| Semantic Kernel| AutoGen or enterprise agent platforms.Define architecture blueprints| solution patterns| reusable components| and best practices.Model Development  EngineeringBuild| fine-tune| and optimize MLDeep LearningNLPLLM-based models using Python and mainstream ML frameworks.Lead experimentation| prototyping| and PoCs for autonomous agents| task decomposition| planning| and self-improving AI workflows.Implement safety| governance| explainability| drift monitoring| and compliance controls.MLOps  GenAI OpsArchitect scalable CICD pipelines for AIMLAgentic solutions.Deploy AI systems using DockerKubernetes| managed ML platforms Collaboration  LeadershipPartner with business teams to translate strategic objectives into AI-driven solutions.Conduct architectural reviews and guide data scientists| ML engineers| and developers.Communicate trade-offs| risks| and architectural decisions clearly to stakeholders.Nice to haveUnderstanding of pharmacy workflowsFamiliarity with healthcare standards FHIR| HL7| NCPDP| EHREMR systems. Exposure to healthcare compliance HIPAA| GxP| FDA regulatory frameworks

Key Skills

Education

Bachelor's degree