AI Architect

Job Description Must Have Technical/Functional Skills

• Experience:
• Must have SI experience with larger IT service provider
• 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., Lang Chain, Lang Graph, CrewAI, Auto Gen).
• 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, Tensor Flow).
• Hands‑on experience with MLOps practices and tools (e.g., Docker, Kubernetes, MLflow).

• 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 Dev Ops 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., Lang Chain, CrewAI), and cloud‑native AI services.
• Thought leadership:
  Stay current with the latest advancements in agentic AI, generative models, and multi‑agent frameworks, driving innovation within the company and potentially presenting at industry conferences.

$180,000-$200,000 per year

• 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 & Training Reimbursement.
• Time Off:
  Vacation, Time Off, Sick Leave & Holidays.
• Legal & Financial Assistance:
  Legal Assistance, 401K Plan, Performance Bonus, College Fund, Student Loan Refinancing.

BACHELOR OF COMPUTER SCIENCE