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)