AI Architect

TATA Consulting Services•New York, NY

47d

About The Position

AI Architect Must Have Technical/Functional Skills Experience: o 10+ years of experience in software architecture or engineering, with at least 5+ years in AI/ML specifically. o Proven experience designing and developing multi-agent AI systems in a production environment. o Significant experience in the healthcare industry, with a deep understanding of clinical workflows, RCM, data standards (HL7, FHIR), and regulated environments. Technical skills: o Expertise in multi-agent orchestration frameworks (e.g., LangChain, LangGraph, CrewAI, AutoGen). o Deep knowledge of LLM architectures, RAG implementation, and techniques for fine-tuning models. o Extensive experience with cloud platforms (AWS, Azure, or GCP) and related AI services. o Strong background in data engineering, including building ETL pipelines and managing vector stores. o Proficiency in Python and relevant AI/ML libraries (e.g., PyTorch, TensorFlow). o Hands-on experience with MLOps practices and tools (e.g., Docker, Kubernetes, MLflow). Roles & Responsibilities System architecture: Define the architectural vision and strategy for agentic AI solutions, designing end-to-end architectures that include model integration, orchestration frameworks, memory systems, and tool-use capabilities. Technical leadership: Guide and mentor cross-functional teams of AI engineers, data scientists, and DevOps specialists on architectural patterns and best practices for building scalable and reliable agentic AI systems. Cloud infrastructure and MLOps: Design and deploy multi-agent AI systems on cloud platforms (AWS, Azure, or GCP), building and managing cloud-native AI pipelines with MLOps best practices for monitoring, evaluating, and scaling agents. Healthcare integration: Lead the integration of agentic AI solutions with existing healthcare systems, and other enterprise platforms, while ensuring data interoperability and security. Responsible AI: Ensure the implementation of strong AI governance, security, and ethical practices throughout the agent lifecycle, including bias mitigation, fairness checks, and compliance with healthcare regulations like HIPAA. Proof of concept and scaling: Lead proof-of-concept (PoC) initiatives to validate new agentic capabilities, then develop strategies to scale successful prototypes into production-ready systems. Technology evaluation: Evaluate and integrate a wide range of open-source and proprietary AI tools and technologies, including vector databases, orchestration frameworks (e.g., LangChain, CrewAI), and cloud-native AI services. Thought leadership: Stay current with the latest advancements in agentic AI, gen erative models, and multi-agent frameworks, driving innovation within the company and potentially presenting at industry conferences. Salary Range: $140,000 $180,000 Year TCS Employee Benefits Summary: Discretionary Annual Incentive. Comprehensive Medical Coverage: Medical & Health, Dental & Vision, Disability Planning & Insurance, Pet Insurance Plans. Family Support: Maternal & Parental Leaves. Insurance Options: Auto & Home Insurance, Identity Theft Protection. Convenience & Professional Growth: Commuter Benefits & Certification & amp; Training Reimbursement. Time Off: Vacation, Time Off, Sick Leave & Holidays. Legal & Financial Assistance: Legal Assistance, 401K Plan, Performance Bonus, College Fund, Student Loan Refinancing. #LI-SP1

Requirements

10+ years of experience in software architecture or engineering, with at least 5+ years in AI/ML specifically.
Proven experience designing and developing multi-agent AI systems in a production environment.
Significant experience in the healthcare industry, with a deep understanding of clinical workflows, RCM, data standards (HL7, FHIR), and regulated environments.
Expertise in multi-agent orchestration frameworks (e.g., LangChain, LangGraph, CrewAI, AutoGen).
Deep knowledge of LLM architectures, RAG implementation, and techniques for fine-tuning models.
Extensive experience with cloud platforms (AWS, Azure, or GCP) and related AI services.
Strong background in data engineering, including building ETL pipelines and managing vector stores.
Proficiency in Python and relevant AI/ML libraries (e.g., PyTorch, TensorFlow).
Hands-on experience with MLOps practices and tools (e.g., Docker, Kubernetes, MLflow).

Responsibilities

Define the architectural vision and strategy for agentic AI solutions, designing end-to-end architectures that include model integration, orchestration frameworks, memory systems, and tool-use capabilities.
Guide and mentor cross-functional teams of AI engineers, data scientists, and DevOps specialists on architectural patterns and best practices for building scalable and reliable agentic AI systems.
Design and deploy multi-agent AI systems on cloud platforms (AWS, Azure, or GCP), building and managing cloud-native AI pipelines with MLOps best practices for monitoring, evaluating, and scaling agents.
Lead the integration of agentic AI solutions with existing healthcare systems, and other enterprise platforms, while ensuring data interoperability and security.
Ensure the implementation of strong AI governance, security, and ethical practices throughout the agent lifecycle, including bias mitigation, fairness checks, and compliance with healthcare regulations like HIPAA.
Lead proof-of-concept (PoC) initiatives to validate new agentic capabilities, then develop strategies to scale successful prototypes into production-ready systems.
Evaluate and integrate a wide range of open-source and proprietary AI tools and technologies, including vector databases, orchestration frameworks (e.g., LangChain, CrewAI), and cloud-native AI services.
Stay current with the latest advancements in agentic AI, gen erative models, and multi-agent frameworks, driving innovation within the company and potentially presenting at industry conferences.

Benefits

Discretionary Annual Incentive.
Comprehensive Medical Coverage: Medical & Health, Dental & Vision, Disability Planning & Insurance, Pet Insurance Plans.
Family Support: Maternal & Parental Leaves.
Insurance Options: Auto & Home Insurance, Identity Theft Protection.
Convenience & Professional Growth: Commuter Benefits & Certification & amp; Training Reimbursement.
Time Off: Vacation, Time Off, Sick Leave & Holidays.
Legal & Financial Assistance: Legal Assistance, 401K Plan, Performance Bonus, College Fund, Student Loan Refinancing.

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