Description
We are seeking a Director, Principal Engineer - Applied AI to drive technical excellence and innovation by leading the design and implementation of robust software solutions, providing mentorship to engineering teams, fostering cross-functional collaboration, and contributing to strategic planning.
The successful candidate will serve as a deep technical expert and hands-on architect responsible for defining technology roadmaps, best practices, and standards for AI/ML adoption across the organization.
Key Responsibilities:
- Serve as the primary code-level reviewer and hands-on architect for complex AI/ML systems and frameworks.
- Define and enforce technology roadmaps, best practices, strategies, and standards for AI/ML adoption.
- Conduct research on context/prompt engineering techniques to translate successful research into reusable engineering frameworks.
- Architect and maintain robust data pipelines and data processing workflows for model training and model tuning.
- Implement and champion MLOps tools and practices.
- Lead the effort to agentize existing systems by incorporating agentic frameworks/stacks and integrating them via A2A, MCP protocol.
- Partner with cross-functional teams to integrate AI/ML solutions into products and services.
- Mentor and coach junior and senior engineers on advanced AI/ML techniques, best practices, and architecture design.
Required Qualifications:
- Bachelor's degree in computer science, engineering, mathematics, or a related discipline.
- 12+ years of experience in Software Engineering, Data Science, or Analytics with 5+ years of experience in AI/ML engineering or related fields.
- Demonstrated experience designing and implementing highly scalable, production-grade AI/ML platforms and systems.
- Deep understanding of Large Language Models (LLMs), LLM training & fine tuning.
- Hands-on experience in GenAI and AgenticAI frameworks.
- Expertise in various AI/ML techniques, such as deep learning, natural language processing, reinforcement learning, and large language models.
- Proficiency in Python, R, or other programming languages for data analysis and AI/ML development.
- Experience with DevOps and CI/CD tools and practices.