Principal Software Engineer - Platform & AI Enablement

Summary

Join Anaplan's Platform & AI Enablement team as a highly experienced engineer to influence the design and implementation of platform capabilities for data processing, AI enablement, and developer acceleration. Collaborate with the architecture function, guide teams in integrating AI/ML capabilities, and bring a product mindset to platform engineering. Provide thought leadership across the full-stack, identify opportunities for innovation, mentor engineers, and participate in various team discussions. Help teams balance speed and sustainability while delivering high-quality work under tight deadlines. This role requires a deep understanding of event-driven architectures, data lakes, and streaming pipelines, along with strong experience integrating AI/ML models into production systems. Anaplan offers a collaborative and innovative work environment.

Requirements

• 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

Responsibilities

• 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

Preferred Qualifications

• Help define the future of a data platform at scale
• Work on cutting-edge AI/ML enablement initiatives
• Collaborate with high-caliber teams across data, engineering, and product
• Influence long-term technology strategy in a high-growth environment