Lead Member of Technical Staff (LMTS) - Security Data Science & ML Engineering

To get the best candidate experience, please consider applying for a maximum of 3 roles within 12 months to ensure you are not duplicating efforts.

Job Category

Job Details

About Salesforce

Salesforce is the #1 AI CRM, where humans with agents drive customer success together. Here, ambition meets action. Tech meets trust. And innovation isn't a buzzword - it's a way of life. The world of work as we know it is changing and we're looking for Trailblazers who are passionate about bettering business and the world through AI, driving innovation, and keeping Salesforce's core values at the heart of it all.

Ready to level-up your career at the company leading workforce transformation in the agentic era? You're in the right place! Agentforce is the future of AI, and you are the future of Salesforce.

Salesforce is the world's #1 AI CRM, where humans and intelligent agents work together to drive customer success. As the company leading workforce transformation in the agentic era, Salesforce is redefining how data, AI, and trust converge at global scale.
Within Salesforce, the Security Engineering organization builds intelligent, data-driven, and AI-powered platforms that protect our global infrastructure and customers. We transform massive volumes of security telemetry into real-time detections, decisions, and automated defensive actions, combining deep security domain expertise with modern data science, machine learning, and agentic AI systems.

Role Overview

We are seeking a hands-on Lead Member of Technical Staff (LMTS) who blends software engineering rigor, data engineering depth, and production-grade machine learning to power agentic security experiences.
This role sits at the intersection of high-throughput data platforms, ML-driven risk intelligence, and autonomous decisioning systems. You will design, build, and operate scalable data and ML services that enable real-time threat detection, automated response, and proactive defense across Salesforce's global ecosystem.
As a senior technical contributor, you will directly shape the architecture, reliability, and safety of AI-driven security systems that reason, decide, and act at machine speed.

Key Responsibilities

Security Data Platforms & Architecture

* Design and implement scalable data models, domain contracts, and schemas with strong guarantees on performance, integrity, lineage, and governance.
* Build and optimize batch and streaming pipelines (ETL/ELT, near-real-time) with clear SLAs on latency, quality, and cost.
* Drive platform reliability through observability primitives including SLIs/SLOs, freshness and completeness checks, lineage tracking, and automated parity tests.

Machine Learning, Analytics & Risk Decisioning

* Develop, validate, and deploy statistical and ML models for security use cases such as anomaly detection, behavioral modeling, and risk scoring.
* Productionize models as reliable services with well-defined APIs, feature stores, versioning, and continuous monitoring for drift, bias, and performance.
* Translate large-scale security telemetry into actionable risk intelligence and automated decisions.

Agentic AI & LLM-Powered Security (Core Focus)

* Design and deliver agentic workflows that combine perception, reasoning, and action to reduce time-to-detection and time-to-mitigation.
* Integrate LLMs with security pipelines to automate root-cause analysis, contextual explanations, investigation summaries, and response orchestration.
* Build multi-agent systems with role specialization, delegation, handoffs, and safe execution boundaries.
* Implement retrieval and memory at scale using RAG, hybrid search, re-ranking, and grounding strategies with strict token and cost controls.

Production Systems, APIs & Integration

* Ship secure, well-tested software that embeds ML and agentic workflows into production services, APIs, and internal platforms.
* Expose read-only and action APIs for downstream systems and dashboards (e.g., executive, SOC, and customer-facing views).
* Integrate with internal tooling and action systems while enforcing idempotency, retries, and side-effect control.

Safety, Reliability & Governance

* Design autonomy envelopes including manual, confirm, and fully automated modes with policy enforcement, approvals, spend caps, and blast-radius limits.
* Build end-to-end observability across agent lifecycles, from signal ingestion through planning, tool execution, and outcome verification.
* Implement reliability patterns such as bounded loops, circuit breakers, dead-letter queues, compensating actions, and deterministic fallbacks.
* Ensure secure-by-design handling of sensitive data, complete audit trails, RBAC/ABAC enforcement, and compliance with privacy and regulatory requirements.

Technical Leadership & Collaboration

* Provide technical leadership through architecture reviews, design discussions, and code reviews.
* Mentor engineers and data scientists, raising the quality bar across data, ML, and agentic systems.
* Partner closely with security engineers, product leaders, and infrastructure teams to translate high-impact security problems into pragmatic, scalable solutions.
* Stay current with data, ML, cloud, and agentic AI trends, introducing tools and patterns that materially improve outcomes.

Required Qualifications

* Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Engineering, or equivalent practical experience.
* 8+ years of experience building and operating large-scale data or software systems with high throughput and low latency.
* Strong proficiency in Python (preferred), Scala, or Java, with excellent software engineering fundamentals.
* Expertise with data and stream processing technologies such as Airflow, Spark, Kafka, Flink, or equivalents.
* Solid SQL skills and experience with at least one NoSQL or distributed data store.
* Practical experience deploying and operating ML systems in production, including monitoring and lifecycle management.
* Cloud experience with AWS, GCP, or Azure and managed data/ML services.
* Strong understanding of statistics and machine learning methods and their real-world tradeoffs.
* Excellent communication skills, with the ability to explain complex technical concepts to diverse stakeholders.
* Working knowledge of data privacy, secure data handling, and regulatory requirements (e.g., GDPR, CCPA).

Preferred & Nice-to-Have Qualifications

* Master's degree in Software Engineering, Data Science, or related field.
* Experience with Salesforce data and analytics platforms such as Data Cloud, Tableau/CRMA, or MuleSoft.
* MLOps and infrastructure experience with Docker, Kubernetes, Terraform, CI/CD pipelines, and canary or blue-green deployments.
* Experience with real-time analytics and streaming security use cases.
* Familiarity with agentic frameworks and patterns (planner/supervisor models, multi-agent orchestration, vector databases, model routing).
* Security domain experience with threat detection, vulnerability intelligence, asset graphs, OCSF, or runtime exploitability.
* Salesforce platform experience (Apex, LWC, APIs) or relevant certifications.
* Open-source contributions or a strong portfolio demonstrating applied ML or data engineering excellence.

Why This Role Matters

This role sits at the frontier of security, data, and agentic AI. You will help define how Salesforce moves from human-driven security operations to machine-speed, autonomous defense systems that operate safely, transparently, and at global scale.
If you are excited about building production-grade ML and agentic systems that protect real users, real data, and real infrastructure, this role offers both technical depth and industry-level impact.

Unleash Your Potential

When you join Salesforce, you'll be limitless in all areas of your life. Our benefits and resources support you to find balance and be your best, and our AI agents accelerate your impact so you can do your best. Together, we'll bring the power of Agentforce to organizations of all sizes and deliver amazing experiences that customers love. Apply today to not only shape the future - but to redefine what's possible - for yourself, for AI, and the world.

Accommodations

If you require assistance due to a disability applying for open positions please submit a request via this Accommodations Request Form.

Posting Statement

Salesforce is an equal opportunity employer and maintains a policy of non-discrimination with all employees and applicants for employment. What does that mean exactly? It means that at Salesforce, we believe in equality for all. And we believe we can lead the path to equality in part by creating a workplace that's inclusive, and free from discrimination. Know your rights: workplace discrimination is illegal. Any employee or potential employee will be assessed on the basis of merit, competence and qualifications - without regard to race, religion, color, national origin, sex, sexual orientation, gender expression or identity, transgender status, age, disability, veteran or marital status, political viewpoint, or other classifications protected by law. This policy applies to current and prospective employees, no matter where they are in their Salesforce employment journey. It also applies to recruiting, hiring, job assignment, compensation, promotion, benefits, training, assessment of job performance, discipline, termination, and everything in between. Recruiting, hiring, and promotion decisions at Salesforce are fair and based on merit. The same goes for compensation, benefits, promotions, transfers, reduction in workforce, recall, training, and education.