Senior AI / GenAI Engineer

Job title: Senior AI / GenAI Engineer Work Location: Denver(CO) Minimum years of experience: 8 TO 10 Would you require the candidates to meet you for in person interview? NO Is Skype/WebEx interview,OK? OK Is this onsite/remote position: ONSITE If onsite, will you be considering relocation candidates: Yes Does this position require Visa independent candidates only? No

Job Description: 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

2. 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

3. 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

4. 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

5. 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, GCP, or Azure AWS Bedrock, SageMaker GCP 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)