Remote Principal GenAI & MLOps Architect

Octave; Madison (AL); On-site; USD 210,000 - 260,000; Full time

Job summary

Octave is seeking a Principal AI/ML Software Engineer to architect and deploy production-grade ML systems for a document-based compliance platform. You will build Generative AI features, design agentic AI workflows, and establish robust MLOps and monitoring across large-scale data.

The role emphasizes cross-functional collaboration, model evaluation, and governance, with a strong focus on explainability and regulatory adherence in regulated industries.

Qualifications

• 5+ years Python production experience with ML libraries, Pandas, NumPy, scikit-learn, PyTorch/TensorFlow.
• Advanced SQL proficiency with complex queries, windows, and optimization.
• Strong ML/NLP foundation including document understanding, text classification, and semantic analysis.
• Hands-on with foundation models (GPT/Claude/Llama), prompt engineering, RAG architectures, vector DBs.
• CI/CD for ML, Docker containerization and end-to-end ML pipelines.

Responsibilities

• Build and deploy Generative AI features using foundation models and latency/cost optimization.
• Design agentic AI systems that autonomously handle compliance workflows and document reviews.
• Integrate LLm evaluation frameworks with development and production systems.
• Build and operate end-to-end ML/Ops pipelines with monitoring and rollbacks.
• Implement explainability dashboards (SHAP/LIME) and regulatory-compliance tooling.
• Collaborate with cross-functional teams to translate business needs into ML solutions.

Skills

Python

SQL

NLP

MLOps

LLM Evaluation

Cloud Computing

Data Visualization

Education

Bachelor's or Master's in CS/DS

Tools

AWS Bedrock

SageMaker

Docker

Kubernetes

Pinecone

Weaviate

Chroma

Job description

Octave is seeking a Principal AI/ML Software Engineer to architect and deploy production-grade ML systems for a document-based compliance platform. You will build Generative AI features, design agentic AI workflows, and establish robust MLOps and monitoring across large-scale data.

The role emphasizes cross-functional collaboration, model evaluation, and governance, with a strong focus on explainability and regulatory adherence in regulated industries.