Principal Software Engineer

Description:

As part of the Platform & AI Enablement team under GPTO Engineering, you’ll report to the Sr. Director Engineering API. This team is accountable for shaping enterprise data architecture, enabling high-performance AI-driven workloads, and acting as a technical bridge between engineering and architecture. This is a hands-on role for a deeply experienced engineer who thrives on solving complex problems and scaling robust platforms.

Your Impact
 

• Influence the design and implementation of platform capabilities for data processing, AI enablement, and developer acceleration across batch, streaming, and real-time systems.
• Collaborate with the architecture function to represent engineering needs and help translate architectural direction into practical implementation patterns.
• Guide teams in integrating AI/ML capabilities—including prompt-based LLM use cases, model inference, and feature pipelines—into scalable platform services.
• Bring a product mindset to platform engineering, ensuring solutions are aligned with customer and business goals.
• Provide thought leadership across the fullstack (React, Java, Python), promoting clean, efficient, and maintainable code.
• Identify and drive opportunities for innovation—whether in development tooling, performance optimization, or new platform features.
• Act as a mentor to engineers across teams, elevating technical standards through code review, design input, and informal leadership.
• Participate in incident retrospectives, technical spike planning, and future-looking strategy discussions.
• Help teams balance speed and sustainability—delivering under tight deadlines without compromising quality.
   

Your Qualifications
 

• 12+ years of software engineering experience, ideally in platform, infrastructure, or data-centric product development.
• Expertise in Apache Kafka, Apache Flink, and/or Apache Pulsar.
• Deep understanding of event-driven architectures, data lakes, and streaming pipelines.
• Strong experience integrating AI/ML models into production systems, including prompt engineering for LLMs.
• Polyglot development capability, with hands-on experience in Java, Python, and modern frontend frameworks such as React.
• Comfort working in cloud-agnostic and hybrid environments.
• Familiar with CI/CD pipelines, GitOps practices, and releasing at speed.
• Strong communication skills—both technical and interpersonal—with the ability to influence without authority.
• Experience working within or across globally distributed teams.