Need submission details for Senior Data Scientist – AI Agent Systems, Woodland Hills, CA, Onsite

Dear Partner,

Good Morning ,
Greetings from Nukasani group Inc !, We have below urgent long term contract project immediately available for Senior Data Scientist – AI Agent Systems, Woodland Hills, CA, Onsite need submissions you please review the below role, if you are available, could you please send me updated word resume, and below candidate submission format details, immediately. If you are not available, any referrals would be greatly appreciated.

Interviews are in progress, urgent response is appreciated. Looking forward for your immediate response and working with you.

Candidate Submission Format - needed from you
Full Legal Name
Personal Cell No ( Not google phone number)
Email Id
Skype Id
Interview Availability
Availability to start, if selected
Current Location
Open to Relocate
Work Authorization
Total Relevant Experience
Education./ Year of graduation
University Name, Location
Last 4 digits of SSN
Country of Birth
Contractor Type

: mm/dd

Home Zip Code

Assigned Job Details

Job Title :Senior Data Scientist – AI Agent Systems
Location: Woodland Hills, CA, Onsite
Rate : Best competitive rate

About the Role

We are seeking a highly skilled Senior Data Scientist with deep expertise in AI agent architectures, large language models (LLMs), and NLP systems to lead the development of next-generation, multi-agent AI solutions in the healthcare domain. This role will focus on designing agent-to-agent (A2A) communication protocols, operationalizing Model Context Protocol (MCP) pipelines, and deploying production-ready AI agents for mission-critical healthcare workflows.

The ideal candidate is a seasoned AI professional who thrives on solving complex challenges at the intersection of LLMs, contextual memory, multi-agent orchestration, and healthcare data systems.

Key Responsibilities

• Design & Architect Multi-Agent Systems: Build and implement Agent-to-Agent (A2A) protocols enabling autonomous collaboration, negotiation, and task delegation between specialized AI agents (e.g., ClaimsAgent, EligibilityAgent, ProviderMatchAgent).

• Operationalize Context Pipelines: Architect and deploy Model Context Protocol (MCP) pipelines that support persistent, memory-augmented, context-rich LLM interactions for complex, multi-turn healthcare use cases.

• Develop Domain-Specific Intelligence: Fine-tune and integrate specialized LLMs and NLP models (e.g., medical BERT, BioGPT) for document understanding, intent classification, and personalized recommendations.

• Build Knowledge-Enhanced AI Systems: Design and implement retrieval-augmented generation (RAG) solutions and structured knowledge libraries to dynamically ground agent responses using both structured (FHIR/ICD-10) and unstructured data sources (EHR notes, chat logs).

• Engineer for Scale & Compliance: Collaborate with data engineers and solution architects to develop scalable, secure, and compliant agentic pipelines aligned with HIPAA, CMS, and NCQA standards.

• Innovate in AI Research: Lead research initiatives in context-aware agents, memory-based reasoning, RLHF (reinforcement learning with human feedback), and long-lived conversational agents.

• Drive Production Deployment: Contribute to robust MLOps pipelines for model versioning, performance monitoring, and continuous improvement in real-world deployments.

Required Qualifications

• Master’s or Ph.D. in Computer Science, Machine Learning, Computational Linguistics, or related field.

• 7+ years of hands-on experience in applied AI, focusing on LLMs, transformers, NLP, or agent frameworks in healthcare.

• Proven expertise in A2A protocol design, LangGraph, AutoGen, CrewAI, or similar multi-agent orchestration platforms.

• Strong practical knowledge of Model Context Protocols (MCP) for persistent conversational memory and modular agent interactions.

• Advanced coding skills in Python with proficiency in Hugging Face Transformers, PyTorch, LangChain, spaCy, or similar ML/NLP libraries.

• In-depth understanding of healthcare data standards such as FHIR, HL7, ICD/CPT, X12 EDI.

• Experience with cloud-native development on AWS, Azure, or GCP, including Kubernetes, Docker, and CI/CD.

• Familiarity with healthcare data workflows including benefit plan structures, claims processing, and eligibility validation.

Preferred Qualifications

• Expertise in MCP + VectorDB integration for dynamic agent memory and retrieval.

• Experience deploying LLM-based agent systems in production or at scale in healthcare settings.

• Prior work with voice AI, conversational navigation systems, or AI-based triage tools.

• Published research, patents, or open-source contributions in agent architectures, LLM orchestration, or contextual AI systems.

Must-Have Skills

• ? AI agent architectures, A2A protocols, MCP – 7+ years

• ? LLMs and NLP (medical BERT, BioGPT, etc.) – 7+ years

• ? Retrieval-Augmented Generation (RAG) – 7+ years

• ? Python & ML/NLP libraries – 7+ years

• ? Healthcare data standards (FHIR, HL7, ICD/CPT, X12 EDI) – 7+ years

• ? Cloud & DevOps (AWS, Azure, GCP, Kubernetes, Docker, CI/CD) – 7+ years

Nancy
Talent Acquisition | Nukasani Group Inc
Tel
Email:

540 W Galena Blvd, Suite 200, Aurora IL 60506.