Principal Engineer, AI Enablement

Principal Engineer, AI Enablement is a senior technical leader responsible for building the infrastructure, tools, and standards that allow teams across an organization to successfully develop, deploy, and scale AI/ML solutions.

This is not just coding it s a mix of:

• Architecture
• Platform engineering
• AI/ML enablement
• Leadership and influence

Key Responsibilities

1. AI/ML Platform Development

• Design and build scalable AI platforms using Amazon Web Services (AWS)
• Enable teams to deploy models via standardized pipelines (MLOps)
• Create reusable frameworks, APIs, and SDKs for AI use cases

2. Data Engineering & Processing

• Work with large datasets using **Python and **SQL
• Build ETL pipelines, data lakes, and feature stores
• Ensure data quality, governance, and accessibility

3. Architecture & System Design

• Define cloud-native architectures (microservices, serverless, containers)
• Optimize performance, scalability, and cost
• Select appropriate AI/ML tools (e.g., SageMaker, Bedrock, etc.)

4. AI Enablement Strategy

• Create best practices for AI adoption across teams
• Guide integration of generative AI, NLP, and predictive models
• Evaluate new AI technologies and recommend adoption

5. Leadership & Mentorship

• Mentor engineers and data scientists
• Lead technical decision-making
• Collaborate with product, business, and executive stakeholders

Required Skills

Core Technical

• Strong experience with AWS services (EC2, S3, Lambda, SageMaker)
• Advanced Python (data processing, APIs, ML frameworks)
• Deep knowledge of SQL and database design
• Experience with distributed systems and large-scale data

AI/ML & MLOps

• Model deployment and lifecycle management
• Familiarity with frameworks like TensorFlow, PyTorch
• CI/CD pipelines for ML systems

Software Engineering

• API design, microservices architecture
• Containerization (Docker, Kubernetes)
• Version control and DevOps practices

Preferred Qualifications

• 8 12+ years total experience (despite 5+ minimum listed)
• Experience with generative AI or LLM platforms
• Background in fintech, healthcare, or enterprise-scale systems
• Master s or PhD in CS, AI, or related field (often preferred, not required)