Principal Software Engineer - PMTS

Own Company

Own Company

Software Engineering

Bengaluru, Karnataka, India

Posted on Jun 6, 2026

Description

Job Description

In Salesforce Trusted Services, nothing is more important to our continued success than the security and privacy of our customers' data. We are an integral part of the Salesforce Customer 360 vision, and our focus and passion is building the next-generation of Salesforce Privacy and Security products.

We are seeking a Principal Member of Technical Staff (PMTS) to join the Data Detect engineering team. In this role, you will serve as the go-to technical leader — owning architecture decisions, setting the technical direction for the product, and driving feature delivery across cross-functional teams. Data Detect is a cutting-edge product designed to automatically scan, identify, and classify sensitive and personally identifiable information (PII) within Salesforce org data — providing robust detection capabilities across standard and custom objects, policy-driven scan orchestration, and AI-powered recognition of sensitive data categories.

As a Principal Engineer, you will own complex, high-impact problems end-to-end — from initial design through production operations — and be a force multiplier for the engineers around you. And with customer trust as our #1 value, you will ensure that quality, performance, security, and observability are not afterthoughts but foundational attributes of everything we ship. If you are passionate about data privacy and thrive on hard engineering challenges at the intersection of security, data, and scale, we invite you to join our team.

What You'll Do

  • Define and drive the technical vision and architecture for Data Detect's scanning platform, detection engines, and API surface.

  • Lead High-Level Designs (HLDs) and shepherd solutions through the Design Review Board (DRB), ensuring architectural decisions meet Salesforce's scale and security standards.

  • Architect and evolve policy-driven PII/sensitive data scanning workflows across Salesforce objects, unstructured files, and Data Cloud data stores.

  • Lead the design and integration of AI-powered detection capabilities — including batch inference APIs and NER (Named Entity Recognition) libraries — across a broad set of global sensitive data categories.

  • Own the evolution of both pattern-based (regex) and AI-based PII detection engines, ensuring global compliance coverage (GDPR, CCPA, HIPAA) with precision and performance.

  • Drive cross-functional feature delivery: align on requirements, resolve dependencies, and unblock teams across time zones as requirements evolve.

  • Architect and maintain REST/Connect APIs consumed by external teams and customers, enforcing high standards for design, versioning, and backward compatibility.

  • Drive performance engineering efforts: profile and optimize multi-threaded scanning pipelines at Salesforce scale.

  • Implement real-time monitoring, alerting, and dashboards for scan job health, detection accuracy, and system reliability.

  • Set the standard for testing and code quality: write and review comprehensive unit, integration, and end-to-end tests.

  • Mentor and grow engineers through design reviews, code reviews, and architectural guidance; help others develop into strong, independent contributors.

  • Collaborate with Product Management, Security, and Legal/Compliance to translate complex privacy and regulatory requirements into sound technical solutions.

  • Proactively identify and retire technical debt, drive systemic improvements, and ensure the platform remains healthy as it scales.

  • Stay abreast of industry trends in data privacy, PII detection, and AI/ML to continuously raise the ceiling of what Data Detect can do.

Required Skills

  • Strong proficiency in Java or any other programming language, with a track record of delivering production-quality, highly scalable systems.

  • Demonstrated ability to architect complex distributed systems — multi-threaded pipelines, asynchronous task management, and fault-tolerant job orchestration.

  • Experience with cloud-native architecture — hands-on with AWS/Hyperforce, Kubernetes, and containerized services.

  • Deep experience building highly scalable, performant microservices and REST APIs at significant scale.

  • Strong experience with database systems and data storage technologies, including efficient querying and managing large data volumes.

  • Proven track record of driving technical strategy and influencing engineering decisions across teams and organizational boundaries.

  • Ability to navigate ambiguity: define requirements, unblock teams, and make sound architectural decisions in a fast-moving product space.

  • Comfortable with log search tools such as Splunk, and familiar with alerting and dashboarding for production systems.

  • Excellent problem-solving and communication skills — able to articulate complex technical trade-offs to both engineers and non-technical stakeholders.

  • A growth mindset and strong mentorship instinct: you make the engineers around you better.

  • Knowledge of software development methodologies (Agile/Scrum) and best practices (TDD, CI/CD, code reviews).

Preferred Skills

  • Familiarity with the Salesforce platform — Shield, Data Cloud, or Salesforce core; knowledge of Apex, Lightning Web Components (LWC), or SFDX is a plus.

  • Experience designing or integrating with AI/ML inference services — batch inference APIs, named entity recognition (NER), or ML-powered text classification pipelines.

  • Deep understanding of PII detection and data classification techniques — regex-based pattern matching, AI-based NER, and global sensitive data taxonomies.

  • Familiarity with privacy and compliance regulations (GDPR, CCPA, HIPAA) and the engineering implications of building compliant systems.

  • Experience with Temporal workflows (or equivalent orchestration frameworks) for durable, distributed job execution.

  • Experience architecting high-volume data processing systems — chunked batch jobs, message-queue-driven pipelines, and async data flows.

  • Understanding of web security (SSL/TLS), API security, and secure data handling practices.

  • Familiarity with observability platforms such as Grafana, time-series databases, and statistics-based alerting at scale.

  • Familiarity with CI/CD frameworks such as Jenkins or Bazel-based build and test systems.