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# Software Engineering - MTS, Trust Intelligence Platform

- **Company:** Salesforce Inc.
- **Location:** San Francisco, CA, United States
- **Experience:** Experienced
- **Salary:** $117,200.0 - $176,700.0
- **Contract:** Permanent contract
- **Skills:** Java (Programming Language), Airflow, Amazon Web Services, Automation of Tests, BigQuery, Cloud Computing, Continuous Integration, Software Debugging, Github, Python (Programming Language), Node.Js, Regression Testing, Ruby, Salesforce.Com, Software Engineering, SQL Databases, Tripwire, Workflow Management Systems, Snowflake, Apache Spark, Kubernetes, Information Technology, Presto, Terraform, Data Pipelines, Databricks, Golang
- **Published:** October 16, 2026
- **Apply:** https://salesforce.wd12.myworkdayjobs.com/External_Career_Site/job/California---San-Francisco/Software-Engineering---MTS--Trust-Intelligence-Platform_JR363027

## About the Role

* Industry Experience: 3+ years in software engineering with strong proficiency in Python and Java, and reading-fluency in at least two of Node.js, Go, and Ruby.
 * Pipeline Engineering: Hands-on experience contributing to data pipelines - batch or streaming - including writing idempotent steps and reasoning about retries.
 * CI/CD: Direct experience building and maintaining CI/CD pipelines with automated test coverage.
 * Repo-wide Automation: Comfort writing scripts or small services that interact with many repositories - opening PRs, parsing diffs, handling CI feedback.
 * Workflow Orchestration and Query Engines: Experience with a workflow orchestrator (Airflow, Dagster, Prefect, or Temporal) and a lakehouse / columnar query engine (Trino, Presto, Spark, Snowflake, BigQuery, Athena, Databricks, or Iceberg).
 * SQL: Non-trivial joins, window functions, CTEs.
 * Individual Impact: End-to-end ownership at the feature level - design, implementation, deployment, and the maintenance work that follows.
 * Educational Background: B.S. in Computer Science, Engineering, or equivalent experience.

Preferred / Bonus Skills

 * Supply Chain Security Standards: Working familiarity with CVE, CVSS v3, EPSS, KEV (CISA), and SBOM formats (SPDX, CycloneDX)
 * Scanner & Remediation Tooling: Direct experience with at least two of Snyk, Trivy, Grype, Dependabot, Renovate, Semgrep SCA, OSV-Scanner, or Dependency-Track.
 * Reachability Analysis: Exposure to reachability tooling (e.g., Semgrep) to prioritize fixes by exploitability rather than raw CVE count.
 * GitHub-at-Scale Automation: Experience driving changes across many repositories through GitHub Actions, Dependabot configuration, or custom bots.
 * Container Supply Chain: Working knowledge of layer-based image scanning and base-image lifecycle management.
 * Cloud Infrastructure: Working experience with AWS, Kubernetes, Terraform, and container-based deployment.

## Description

Pipeline Development & Operations

 * Contribute to data pipelines that ingest vulnerability data, dependency manifests, SBOM artifacts, and deployment metadata into a queryable analytics store.
 * Build and maintain batch and streaming jobs with idempotent steps, retries, and clear failure modes.
 * Operate what you ship: on-call for the pipelines you own, debug production failures, and reduce toil through automation.

Repository-wide Automation

 * Build scripts and small services that interact with many repositories at once - opening PRs, parsing diffs, reading CI feedback, and reconciling the results back into a central store.
 * Author and maintain CI/CD pipelines with automated test coverage so remediation PRs can be reviewed and merged with confidence.
 * Resolve attribution issues at the source rather than patching symptoms downstream.

Collaboration & Communication

 * Partner with service owners to land dependency upgrades, triage breakage, and raise the quality of generated fix PRs.
 * Translate noisy scanner output into prioritized, actionable work for engineering teams.
 * Write clear design docs, runbooks, and PR descriptions; keep documentation current when behavior changes.

Quality & Growth

 * Write Python and Java code that matches the conventions of the existing codebase and holds up under review.
 * Add regression tests for every bug you fix; treat failing tests as signal rather than noise.
 * Learn the supply chain domain on the job - vulnerability lifecycle, dependency resolution, artifact provenance - and bring that knowledge back into the pipelines you build.