AI Engineer |Gen AI (healthcare Domain)_Hybrid@Denver(CO)

Job title: AI Engineer |Gen AI (healthcare Domain)

Work Location: Denver(CO)

Hybrid

Minimum years of experience: 8 TO 10

Role Overview

We are looking for a Senior AI / GenAI Engineer with strong experience in production-grade ML systems, Generative AI (LLMs, RAG, Agents), and enterprise automation. The ideal candidate will have hands-on expertise in deploying scalable AI systems, ensuring reliability, monitoring, and governance, and working across domains such as healthcare or enterprise IT operations.

Key Responsibilities: 1. GenAI & LLM Engineering

Design and implement RAG pipelines using vector stores (Pinecone, FAISS, etc.) Build and deploy LLM-based applications using OpenAI, Claude, LLaMA, or similar Develop multi-agent systems (LangChain, LangGraph, CrewAI, Autogen) Optimize prompts, retrieval strategies, and model performance for production use

• ML Engineering & Data Science

Build and deploy ML models across

Classification, Regression, NLP, Time-series, and Anomaly Detection Perform EDA, feature engineering, and experiment design Implement A/B testing frameworks and performance evaluation pipelines

• MLOps & Productionization

Implement end-to-end ML lifecycle

Model training, testing, deployment, monitoring, and rollback Use tools like MLflow, CI/CD pipelines (GitHub Actions/Azure DevOps) Ensure model versioning, reproducibility, and governance Manage online & batch inference systems

• Observability & Reliability

Build monitoring systems for

Model drift

Performance degradation

Hallucination detection in LLMs

Define incident response and rollback strategies Maintain dashboards and alerting frameworks

• AI Safety & Compliance

Implement AI guardrails

PII/PHI detection

Content filtering

Prompt injection defense

Ensure compliance with regulatory standards (e.g., HIPAA) 6. Cloud & Infrastructure

Deploy solutions on AWS, Google Cloud Platform, or Azure

AWS Bedrock, SageMaker

Google Cloud Platform Vertex AI

Azure OpenAI / AI Foundry

Build scalable infra using Docker, Kubernetes, Terraform 7. Enterprise Automation (RPA Integration)

Design and support RPA workflows using Automation Anywhere / UiPath Integrate AI/ML models into automation pipelines Manage bot lifecycle, orchestration, and governance 8. Collaboration & Leadership

Work with product, data, and engineering teams to deliver scalable solutions Mentor junior engineers and review technical designs Create documentation (PDDs, SDDs, architecture designs) Required Skills

Core Technical Skills

Strong Python development (FastAPI, ML libraries) ML frameworks: PyTorch / TensorFlow / Scikit-learn GenAI stack: OpenAI, Claude, LLaMA, Hugging Face RAG systems and vector databases (Pinecone, FAISS, etc.) MLOps & Systems

MLflow, model registry, CI/CD pipelines

Experiment tracking and automated testing Deployment patterns (batch + real-time inference) Data & APIs

SQL, REST/SOAP APIs

Experience with enterprise systems (SAP, Salesforce, etc. is a plus)

Nice to Have

Healthcare domain experience (HIPAA compliance, clinical or claims data) Experience with agentic workflows & human-in-the-loop systems Hands-on experience in cost optimization for LLM workloads RPA certifications (Automation Anywhere / UiPath)