Senior Principal Software Engineer
Apperian
About Digital.ai
Digital.ai is the only AI-powered software delivery platform purpose-built for the enterprise, enabling the world’s largest organizations to build, test, secure, and deliver high-quality software. By unifying AI-driven insights, automation, and security across the software development lifecycle, Digital.ai empowers enterprises to deliver innovation with confidence. Trusted by 5,000 global enterprises, Digital.ai is redefining how enterprises build better software in an AI-driven world. Additional information about Digital.ai can be found at digital.ai and on Twitter, LinkedIn, and YouTube.
About the Role:
This position is an exciting opportunity to join the Predictive Intelligence division of Digital.ai,
a 9-time Leader in Gartner Magic Quadrant for Enterprise Agile Planning, Digital.ai unifies, secures, and generates predictive insights across the software lifecycle for Global 2000 enterprise customers.
Our mission is to unlock endless digital possibilities by harmonizing the delivery of software. Our vision is to be THE enterprise platform for AI driven software development.
Position Summary
Digital.ai is looking to hire Senior Principal Software Engineer with 12-16 years of experience to provide strategic and hands-on technical leadership across platform, data, and AI systems. This role owns end-to-end system architecture, drives cross-organization technical direction, and ensures scalable, secure, and highly integrated solutions. The ideal candidate combines deep software engineering expertise with strong data, AI, and platform architecture skills, and has a proven ability to influence engineering at scale.
Key Responsibilities
- Design and implement enterprise-scale architectures for web applications, data platforms, and AI systems.
- Solve complex system design and integration challenges across distributed and multi-platform environments.
- Design and implement robust data APIs and service integrations across platforms.
- Architect and implement modern data platforms using Delta Lake, data warehouses, and distributed systems.
- Design, implement, and support ML, MLOps, and AI/LLM workflows, including feature stores, embeddings, and inference pipelines.
- Ensure high standards for reliability, performance, security, observability, and data quality.
- Build and maintain CI/CD pipelines using GitHub Actions and modern DevOps practices.
- Apply deep hands-on expertise in Java, Python, and modern backend frameworks to deliver high-quality solutions.
- Improve automation, monitoring, and operational reliability across systems.
- Follow and contribute to best practices for code quality, testing, and release management.
Required Qualifications
- 12 to 16 years of professional software engineering experience.
- Expert-level software engineering and system design experience.
- Strong hands-on experience with Java and Python.
- Proven experience building web applications and backend services.
- Deep knowledge of data warehousing, ETL/ELT, and data modelling.
- Hands-on experience with Delta Lake and distributed data processing (Spark/PySpark).
- Experience with cloud platforms (AWS, Azure, or GCP).
- Strong experience designing and managing Data APIs and system integrations.
- Working knowledge of ML workflows and AI/LLM systems.
- Experience with CI/CD pipelines, especially GitHub Actions.
Nice-to-Have Qualifications
- Domain knowledge of ITSM & DevOps applications.
- Familiarity with MLOps concepts such as model monitoring, data drift detection, or automated retraining pipelines.
- Strong background in distributed systems and microservices architectures.
- Experience with LLM-based systems, such as embeddings, vector databases, RAG pipelines, and prompt orchestration.
- Experience designing and operating large-scale, multi-tenant data or AI platforms.
- Hands-on experience with streaming platforms (Kafka, Flink, Spark Structured Streaming).
- Familiarity with data governance, lineage, and compliance frameworks.
- Proven experience driving cross-team technical initiatives and influencing architectural decisions.