Principal AI & DevOps Engineer

About this role

We are seeking a seasoned Principal AI & DevOps Engineer to join our team. You will be a strategic builder and technical leader who brings deep expertise in turning complex AI/ML concepts into scalable, production-grade systems for enterprise operations.

First 30 Days — Strategic Discovery & Architecture Assessment

• Enterprise Systems Audit: Rapidly assess our existing technical landscape to identify gaps and high-leverage opportunities.
• Cross-Functional Stakeholder Engagement: Lead discovery sessions across business units to define a prioritized roadmap for AI/ML intervention.
• Technology Evaluation & Benchmarking: Evaluate current toolchain using deep knowledge of emerging technologies and best practices.
• Strategic Value Mapping: Assess where generative AI can reduce overhead or create competitive advantage.

Beyond 30 Days — Build, Lead, and Scale

• Full-Stack AI Application Development: Architect production-quality applications using Python backends and JavaScript/Flutter frontends with a focus on performance and UX.
• Context Engineering & LLM Optimization: Design strategies for orchestrating enterprise data, memory systems, tool outputs, and prompt chaining within LLM context windows to produce accurate, structured outputs at scale.
• End-to-End Pipeline Ownership: Own the full deployment lifecycle. Implement CI/CD pipelines for LLM applications with automated testing frameworks.
• Data Engineering & ML Lifecycle Management: Drive data quality, pipeline integrity, and dataset governance to fuel deployed models through validation, query optimization, and input management.
• Observability & Performance Engineering: Establish monitoring using tools like AWS CloudWatch, track AI performance against KPIs, and deliver executive-ready dashboards connecting system health to business outcomes.
• Technical Leadership & Knowledge Sharing: Mentor peers through code reviews, lead architectural discussions, and present solutions during stakeholder demos.

Required Qualifications

Bachelor's or Master's degree in Computer Science or equivalent field with 8–12 years of hands-on experience in full-stack development. Must have proven DevOps & Automation expertise including CI/CD tooling, deployment workflows, and Infrastructure as Code (IaC) in production environments.