Work Location: Denver(CO)
Minimum years of experience: 8 TO 10
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
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
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)
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
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
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)