Software Engineering MTS

Salesforce.com, inc.; Bellevue (WA); Hybrid; USD 117,000 - 176,000; Full time

Job summary

Salesforce seeks an MTS Engineer to design a secure, cloud-native data platform that processes security signals from 15+ ecosystems and scales to handle 600 TB daily in real-time. You will build robust pipelines, apply AI/ML workflows, and advance governance and remediation automation across the enterprise.

Lead engineering initiatives, mentor peers, and champion secure, scalable architectures with strong collaboration across Security, IT, and Product teams.

Qualifications

• Bachelor's or Master's degree in Computer Science or Engineering (or equivalent experience).
• 2+ years in SaaS, PaaS, or IaaS software development.
• Experience with distributed systems, data engineering, and security fundamentals.

Responsibilities

• Design and architect a scalable, secure data platform ingesting diverse security data.
• Build data pipelines across multiple environments (AWS, GCP, Salesforce, vendor systems).
• Integrate AI/ML and LLM-driven capabilities with evals, guardrails, and cost/latency tradeoffs.
• Collaborate with cross-functional teams to align data platform with goals.

Skills

Distributed systems

Data engineering

Docker/EKS

Terraform/IAC

Spark/Kafka

Python/Java/Go

Security concepts (SSO/SAML/OAuth)

LLMs/ML in production

Agentic tooling (Claude Code/Copilot)

Linux administration

Communication skills

Agile / teamwork

Education

Bachelor's or Master's in CS/Engineering

Tools

EKS

Terraform

Puppet

Apache Spark

Kafka

Job description

The Data Security Fabric team is seeking a Member of Technical Staff (MTS) Engineer to help design and build a secure, cloud-native, and highly scalable Data Platform designed to measure, mitigate, and reduce enterprise risk. By unifying disparate security data across the organization, our platform will provide actionable insights to proactively identify risks and automate remediation efforts.

As an MTS Engineer on our team, you'll be responsible for designing and implementing a robust data platform that collects and processes critical security signals from a wide range of sources. This includes collecting and processing 600 TB of data daily in real-time streaming — spanning application logs across all Salesforce products, comprehensive asset information (hardware and software) across Salesforce, vulnerability data from large-scale scanning tools such as Tenable and Prisma, user identity and access data, security signals from 10+ Salesforce platforms (e.g., Core, Hyperforce, Data Cloud, Slack, Tableau, Heroku, MuleSoft), and other security signals from over 15 different environments like AWS, GCP, CRM systems, and third-party vendor platforms.

You'll leverage cutting-edge technologies to build the next-generation security data platform and create a vendor-agnostic core security system. AI and machine learning are first-class capabilities of this platform — you'll help design LLM- and ML-driven workflows for security signal enrichment, anomaly detection, risk scoring, and automated triage, and integrate agentic patterns (RAG, tool-use, evals) into the platform's remediation and investigation flows. You'll also help establish data governance and quality frameworks to support risk management, regulatory compliance, and continuous security improvement across the enterprise.

This is an exciting opportunity for an engineer with a passion for distributed systems, big data processing, AI/ML, and security. You'll play a key role in shaping the future of security at Salesforce, helping ensure the platform's scalability, reliability, and alignment with industry best practices. Your work will directly impact Salesforce's security strategy — driving innovation, improving risk management, using AI to accelerate detection and response, and enabling automation of security remediation across the organization.

If you're looking to grow your technical expertise in cloud-native systems, cybersecurity, big data processing, and applied AI, this role offers strong opportunities for personal and professional development, along with meaningful visibility and business impact.

Responsibilities

• Learn and adapt to Salesforce's security strategies, goals, objectives, and capabilities to improve security posture.
• Lead the design and architecture of a highly scalable and secure data platform that ingests and processes diverse security data sources across 10+ Salesforce platforms and 15+ external environments.
• Build and optimize data pipelines to collect, store, and analyze security signals from tools and platforms (e.g., vulnerability scanners, asset management systems, identity and access control systems) running across multiple environments (AWS, GCP, Salesforce, CRM, vendor systems, etc.).
• Design and integrate AI/ML and LLM-driven capabilities into the platform — including RAG over security data, agentic triage/remediation workflows, anomaly detection, and risk scoring — with strong attention to evals, guardrails, and cost/latency tradeoffs.
• Work closely with cross-functional teams (e.g., Engineering, Security Operations, Risk Management, Product Security, and Data Science) to align the data platform with business and security goals.
• Participate in Agile development, including daily syncs.
• Support the team's engineering excellence through code reviews and mentoring for team members at all levels.
• Provide technical leadership to a team of engineers, driving best practices in software development, security, AI-assisted development, and cloud-native architecture. Mentor engineers at earlier career stages, fostering a culture of continuous learning, innovation, and excellence.
• Champion effective use of AI-assisted development tools (e.g., Claude Code, Cursor, Copilot) across the team — establishing patterns for agent-driven workflows, code review, and productivity while maintaining code quality and security.
• Own and deliver initiatives that add new features to meet growing product demands.
• Adapt quickly to changing requirements, priorities, and strategies.
• Advocate for security and secure practices throughout Salesforce, including secure AI/agent design (prompt injection defenses, least-privilege tool access, data handling for LLM contexts).

Required Skills/Experience

• 2+ years of industry experience for MTS, including 2+ years in SaaS, PaaS, or IaaS software development
• Bachelor's or Master's degree in Computer Science or Engineering (or equivalent experience)
• Distributed systems and data engineering expertise, including:
• High-performance, high-availability (99.99%), highly fault-tolerant systems
• Docker-based development, especially with EKS
• Configuration management systems, including Infrastructure-as-Code (IAC), Terraform, Puppet
• Data technologies: Apache Spark & Kafka, Hadoop, SQL/NoSQL
• Programming proficiency in object-oriented and multi-threaded development using at least one of: Python, Golang, Java/Scala
• Demonstrated expertise applying systems patterns (e.g., client-server, N-tier, primary/secondary, MVC) and API construction (e.g., Swagger, OpenAPI)
• Experience developing and managing software on Linux (e.g., CentOS or RHEL)
• Strong fundamentals in security concepts: authentication/authorization frameworks (e.g., SSO, SAML, OAuth), secure transport (e.g., TLS), identity management (e.g., certificates, PKI)
• Hands-on experience integrating LLMs or ML models into production systems, including at least two of: RAG pipelines, agent/tool-use frameworks (e.g., MCP, LangGraph), prompt engineering, evals/observability for LLM apps, fine-tuning, or embeddings/vector stores
• Demonstrated fluency with agentic coding tools (Claude Code, Cursor, Copilot, or equivalent) as a daily driver, with the ability to guide the team on effective and safe usage patterns
• Excellent oral and written communication skills
• Ability to manage multiple projects, meet deadlines, and adapt to shifting priorities
• Strong collaborator who values team success alongside individual contributions
• Ability to translate strategic or operational goals into technical and tactical requirements and architecture design

Preferred / Nice-to-have

• Experience applying AI/ML to security use cases — e.g., anomaly detection, alert triage, vulnerability prioritization, or SOC automation
• Experience with MCP (Model Context Protocol), tool-use frameworks, or building agentic workflows on top of security data
• Familiarity with LLM cost/latency optimization, guardrails, prompt-injection defense, and evaluation frameworks
• Experience with vector databases and embedding-based retrieval over structured/unstructured security data

Pursuant to the San Francisco Fair Chance Ordinance and the Los Angeles Fair Chance Initiative for Hiring, Salesforce will consider for employment qualified applicants with arrest and conviction records.

In the United States, compensation offered will be determined by factors such as location, job level, job-related knowledge, skills, and experience. Certain roles may be eligible for incentive compensation, equity, and benefits. Salesforce offers a variety of benefits to help you live well including: time off programs, medical, dental, vision, mental health support, paid parental leave, life and disability insurance, 401(k), and an employee stock purchasing program. More details about company benefits can be found at the following link: https://www.salesforcebenefits.com.

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The typical base salary range for this position is $117,200 - $176,700 annually.

The range represents base salary only, and does not include company bonus, incentive for sales roles, equity or benefits, as applicable.

We can't wait to meet you!