GEN AI Solution Architect

EXL; Dallas (TX); On-site; USD 140,000 - 190,000; Full time

Job summary

EXL in Dallas, TX seeks an experienced AI Architect to design end-to-end GenAI solutions for healthcare, covering data ingestion, model development, deployment, and monitoring.

You will lead pre-sales, collaborate with data science teams, and mentor engineers while ensuring HIPAA and data privacy compliance.

This role requires hands-on work with LLMs, RAG pipelines, cloud services, and modern microservices to deliver scalable healthcare AI platforms.

Qualifications

• Strong foundation in AI/ML, Deep Learning, and GenAI architectures.
• Hands-on experience with LLMs, RAG pipelines, vector databases, and AI agents.
• Experience with unstructured data processing (NLP, OCR, Intelligent Document Processing).
• Solid understanding of data engineering & analytics stacks (data lakes, data warehouses, ETL/ELT pipelines).
• Proficiency with cloud platforms (AWS / Azure / GCP) and AI services.
• Experience with microservices, APIs, containerization (Docker/Kubernetes).
• Knowledge of payer and provider workflows.
• Exposure to regulatory and compliance requirements in healthcare.
• Proven experience delivering AI solutions in healthcare operations or clinical workflows.

Responsibilities

• Design end-to-end AI / GenAI architectures covering data ingestion, feature engineering, model development, deployment, and monitoring.
• Lead solutioning for healthcare use cases such as claims processing and payment integrity; care management and population health.
• Architect AI agents and RAG-based solutions using LLMs for unstructured healthcare data.
• Collaborate with data science teams on model selection, prompting, and orchestration strategies.
• Ensure HIPAA, PHI/PII, security, governance, and AI risk compliance.

Skills

AI/ML

GenAI architectures

LLMs

RAG pipelines

Vector databases

NLP

OCR

Document processing

Data engineering

ETL/ELT

Cloud platforms

AWS

Azure

GCP

Docker

Kubernetes

APIs

Microservices

Healthcare workflows

Compliance

Tools

Docker

Kubernetes

APIs

Vector databases

Job description

Responsibilities for Internal Candidates

• Design end‑to‑end AI / GenAI solution architectures covering data ingestion, feature engineering, model development, deployment, and monitoring.
• Lead solutioning for healthcare use cases such as:
• Claims processing & Payment Integrity
• Care Management & Population Health
• Clinical document processing and summarization
• Provider & member analytics
• Architect agentic AI and RAG‑based solutions using LLMs for unstructured healthcare data (clinical notes, policies, contracts, medical records).
• Translate business problems into AI‑driven architectures, ensuring alignment with ROI, scalability, and regulatory requirements.
• Define reference architectures, NFRs, and technology standards for AI platforms.
• Collaborate with data science teams on:
• Model selection and evaluation
• Prompt engineering and orchestration strategies
• Ensure solutions comply with HIPAA, PHI/PII, security, governance, and AI risk frameworks.
• Provide technical leadership during pre‑sales, client workshops, proposals, and solution walkthroughs.
• Mentor engineers and junior architects; review designs and ensure architectural best practices.
• Stay current with emerging trends in GenAI, agentic workflows, healthcare AI regulations, and cloud AI services.

Qualifications

Core Technical Skills

• Strong foundation in AI/ML, Deep Learning, and GenAI architectures
• Hands‑on experience with LLMs, RAG pipelines, vector databases, and AI agents
• Experience with unstructured data processing (NLP, OCR, Intelligent Document Processing)
• Solid understanding of data engineering & analytics stacks
• (Data lakes, data warehouses, ETL/ELT pipelines)
• Proficiency with cloud platforms (AWS / Azure / GCP) and AI services
• Experience with microservices, APIs, containerization (Docker/Kubernetes)
• Knowledge of payer and provider workflows
• Exposure to regulatory and compliance requirements in healthcare
• Proven experience delivering AI solutions in healthcare operations or clinical workflows