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 seeking a Principal Software Engineer with 8-12 years of experience to provide technical leadership in designing and building large-scale data, analytics, and AI/LLM platforms. This role requires deep expertise in data engineering, strong software architecture skills, and the ability to influence technical direction across teams. You will drive platform-level decisions, mentor senior engineers, and enable advanced analytics, ML, and AI use cases.

Key Responsibilities

• Build and optimize large-scale batch and streaming data pipelines.
• Implement modern data lake and warehouse solutions using Delta Lake and cloud-native services.
• Apply best practices in data modelling, ETL/ELT strategies, and schema evolution.
• Design, implement, and support ML and AI/LLM workflows, including feature engineering, embeddings, vector data, and inference pipelines.
• Ensure high standards for data quality, observability, performance, and security.
• Collaborate closely with Data Science and ML teams to support scalable model training and deployment.
• Participate in design reviews, architectural discussions, and technology evaluations.
• Mentor senior and junior engineers

Required Qualifications

• 8-12 years of professional software engineering experience.
• Deep expertise in software engineering and system design.
• Strong foundation in data warehousing and data modelling.
• Hands-on experience with Delta Lake and distributed data processing (Spark/PySpark).
• Extensive, expert-level proficiency in programming languages such as SQL, Python, and Java.
• Experience with cloud platforms (AWS, Azure, or GCP).
• Working knowledge of ML workflows and AI/LLM concepts.
• Experience designing highly available, scalable systems.

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.
• 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).
• Experience building ETL/ELT pipelines and data platforms.
• Familiarity with data governance, lineage, and compliance frameworks.
• Proven experience driving cross-team technical initiatives and influencing architectural decisions.