Position Summary

This position is an exciting opportunity to join the Application Security division of Digital.ai, an industry leader specializing in client-side application protection. Our products embed security directly into applications, enabling them to defend themselves in untrusted environments. We are seeking a highly experienced Principal Software Engineer with expertise in modern web portal development, distributed event-processing systems, real-time analytics platforms, and AI/ML-driven data engineering workflows. The ideal candidate will help architect and optimize intelligent, data-intensive systems that support large-scale telemetry and security analytics. Experience with React, Node.js, Kafka, AWS Lambda, cloud-native engineering, and the use of AI/ML techniques to enhance data processing and insight generation is required.

What You Will Be Doing

You will join a team of cloud-native engineers building scalable, secure, and reliable cloud services powering our in-app protection products. Our services process billions of security events daily from more than 10 million devices worldwide.

As a full-stack Principal Engineer, you will:

• Drive architecture and implementation across the web stack, distributed systems, and AI-assisted analytics workflows.
• Leverage AI/ML techniques to strengthen event processing, anomaly detection, and data enrichment.
• Influence technical strategy across multiple teams, particularly around intelligent pipelines and analytics.
• Work in a fast-paced Agile/Scrum environment with frequent releases and high impact.

Primary Responsibilities

Web Application & Portal Engineering

• Lead the architectural design and development of scalable, secure web applications using React, Node.js, and TypeScript.
• Develop modular, maintainable UI components and back-end services aligned withengineering standards.
• Ensure adherence to performance, accessibility, and security best practices.Event Processing & Streaming Systems
• Architect and maintain distributed, event-driven systems using Apache Kafka, AWS Lambda, and related AWS services.
• Implement high-throughput pipelines for event ingestion, transformation, and enrichment.
• Apply AI-assisted techniques (e.g., automated anomaly scoring, content classification, behavioural clustering) to enhance streaming workflows.
• Ensure reliability, observability, and resilience across all streaming components.

Real-Time Analytics & Intelligent Data Engineering

• Design and support systems that deliver real-time analytics based on streaming and operational data.
• Collaborate with data engineering, analytics, and product teams to define schemas, telemetry models, KPIs, and AI-enriched data signals.
• Integrate lightweight ML models, heuristics, or AI-based scoring mechanisms intodashboards, alerts, and internal tools.
• Build data pipelines that support ML-assisted insights, including featurecomputation, data quality validation, and intelligent filtering.
• Work with ML frameworks or cloud AI services to operationalize models whereappropriate (e.g., anomaly detection, threat classification, event clustering).

Technical Leadership

• Drive architectural decisions involving high-scale distributed systems and AI/ML-enabled analytics components.
• Provide guidance on coding standards, intelligent pipeline patterns and data engineering best practices.
• Conduct design and code reviews, contributing to continuous process improvement.
• Mentor junior engineers and contribute to organization-wide technical initiatives.

Required Qualifications

• 8 to 12 years of professional software engineering experience.
• Advanced proficiency in React, Node.js, JavaScript/TypeScript, and modern front-end and back-end development practices.
• Hands-on experience with Apache Kafka, AWS Lambda, and event-driven serverless architectures.· Experience working with AWS API Gateways.
• Strong understanding of distributed systems, microservices, and REST/GraphQL API design.
• Experience with containerization (e.g., Docker), CI/CD pipelines, and AWS cloud-native environments.
• Experience on deploying and operating cloud-native applications on Kubernetes (EKS preferred).
• Experience with Postgres as a backend data store.
• Experience applying AI/ML techniques within data engineering or analytics workflows (e.g., anomaly detection, data classification, outlier scoring, clustering, or intelligent event enrichment).
• Proficiency using Python or cloud AI/ML services for productionizing lightweight models or heuristics.
• Strong background in unit, integration, and automated testing.
• Demonstrated ability to design scalable, highly available, and fault-tolerant systems.

Nice-to-Have Qualifications

• Domain knowledge of application security and security telemetry.
• Understanding the security threats and mitigation techniques.
• Experience with Apache Druid, ClickHouse, Snowflake for real-time analytics and OLAP workloads.
• Familiarity with MLOps concepts such as model monitoring, data drift detection, or automated retraining pipelines.
• Experience integrating LLMs or embedding-based techniques into data pipelines or developer tools
• Experience with DynamoDB, including NoSQL design patterns.
• Familiarity with AWS services such as ECS/EKS or Terraform.
• Understanding of event sourcing, CQRS, and advanced streaming patterns.
• Experience with observability tools (CloudWatch, Grafana, or Prometheus).

Digital.ai is firmly committed to merit-based hiring. We maintain compliance with US and International laws. We welcome everyone from all backgrounds, including age, race, color, gender, identity, gender expression, sex, pregnancy, national origin, ancestry, religion, physical or mental ability, medical condition, sexual orientation, marital status, citizenship status, protected military or veteran status, and believe that diversity is the foundation of innovation. 

For individuals with disabilities who would like to request an accommodation, please advise us within your job application or cover letter. 

FRAUD PREVENTION ALERT: Please note that Digital.ai does not use third party recruiters. In our efforts to protect you against possible impersonation please check the email address or are contacted by an unfamiliar/third party requesting please reach our directly to Digital.ai.  

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.

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.