Technology Lead | OpenSystem | Python - OpenSystem

Job title: AI Engineer (CAN submit Visa dependent profiles)
Work Location: Denver(CO)
Vendor Rate: #### USD
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)

Project Code: SDIT Nebula Dev amp Support