eTeam

AI/ML & Agentic Architecture Design 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.
Essential Skills: AI| ML| Gen AI| AWS
Desirable Skills:
Keyword:
Skills: Digital : Amazon Web Service(AWS) Cloud Computing~Digital : Artificial Intelligence(AI)~
Experience Required: 10 & Above