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Job Category
Software Engineering
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 seeking a Lead Software Engineer (LMTS) to join the Agentforce Process Intelligence team, building process mining and optimization capabilities within the Agentforce platform. You will act as a technical leader across one or more teams, owning the end-to-end architecture of backend services and full-stack applications that enable enterprise customers to discover, simulate, and optimize their business processes at scale.
This role sits at the intersection of large-scale distributed systems, data-intensive analytics, and cloud platform engineering. You will be a leading technical representative across the application stack — negotiating interfaces with peer teams, driving architectural alignment across the product, and setting the bar for non-functional quality (availability, multi-tenancy, security, performance) across Java and python application services.
Drive the architecture, design, implementation, and delivery of secure, highly scalable backend services deployed on Kubernetes in a cellular, multi-AZ cloud architecture, and act as the technical leader for one or more teams.
Set the long-term technical vision ( 2RR scope) for the Backend / Full-Stack pillar, including the evolution of Java-based application services (Spring Boot, Hibernate 6+, JPA) and companion microservices toward a pooled multi-tenant model with end-to-end tenant isolation.
Own the architecture for Python-based data processing services and ETL pipelines that feed large-scale data ingestion and transformation, ensuring contracts with the data platform layer are clean and forward-compatible.
Architect database consolidation and migration efforts using PostgreSQL, Liquibase, and connection pooling strategies, and validate the technical plans your teams produce against scalability, availability, and tenant-isolation requirements.
Drive integration with big data query and processing layers (distributed query engines, columnar storage formats) so analytical workloads route correctly and meet SLOs.
Architect authentication and authorization integrations with identity providers (session-based auth, mTLS for service-to-service communication) and partner with Security on threat modeling, AppSec, and AI safety guardrails for new features.
Define SLIs and SLOs for the team's features and services in partnership with Product, design rollout strategy and telemetry that spans pre-release / canary / stagger periods, and lead service ownership: on-call rotations, ops and readiness reviews, runbooks, and automation.
Set test strategy across the pillar — unit, integration, functional, regression, and performance — and approve test plans for cross-team initiatives.
Write architectural documents, design specifications, and test plans for projects that span multiple teams; lead and participate in design reviews; and provide constructive feedback on peer teams' designs.
Provide technical coaching and mentorship to LMTS and SMTS engineers on the team and on peer teams, primarily through reviews; recognize which large designs to delegate and which to implement yourself.
Manage the technical backlog so that team goals and long-term technical debt are both addressed, and propose standards and best practices where they don't yet exist across the organization.
Represent the team to VP-level engineering leadership, Product, and external stakeholders — clearly and concisely explaining initiatives, high-level architectures, and trade-offs; act as a technical liaison for Customer Trust when needed.
Champion Customer Trust within the team: reinforce non-functional requirements, occasionally engage directly with customers to validate that features solve real problems, and lead critical problem management to limit customer impact.
10+ years of professional software development experience, with a proven track record of shipping enterprise SaaS at scale and operating in a technical leadership capacity.
Strong proficiency in Java and/or Python, with production-level fluency across multiple languages in real systems.
Deep experience with Java backend frameworks: Spring Boot, Hibernate/JPA, Tomcat, and relational database integration (PostgreSQL, MySQL).
Architectural expertise in relational databases, data modeling, schema migration tools (Liquibase, Alembic), and query optimization.
Hands-on experience designing, operating, and evolving highly available distributed systems on AWS or comparable cloud platforms, with 99.99%+ availability targets.
Expertise in containerization and orchestration (Kubernetes, Docker) in production environments.
Expertise in REST API design, service mesh architectures, and mTLS / zero-trust security models.
Experience leveraging AI capabilities for SDLC automation, such as context-aware code generation that aligns with architectural patterns, code review workflows, automated testing, vulnerability detection and remediation, and/or CI/CD optimization.
Demonstrated ability to drive proactive threat modeling and partner with security/compliance on AppSec, vulnerability management, and AI safety considerations for new features.
Hands-on experience with automated testing including unit, integration, and functional testing (JUnit, pytest, Selenium, Playwright), and a track record of defining test strategy for complex, cross-team systems.
Proven ability to lead technical initiatives across multiple teams, mentor LMTS/SMTS engineers, and drive architectural alignment across organizational boundaries.
Exceptional communication skills — including the ability to present technical strategy and trade-offs to VP-level engineering leadership, Product, and external customers.
A related technical degree required.
Familiarity with multi-tenant SaaS ecosystems and cloud platform engineering, including tenant-isolation patterns across database, cache, and storage layers.
Proficiency in Python: solid experience with Python backend/data frameworks (SQLAlchemy, Alembic, FastAPI or Flask) and data processing libraries (PySpark, Pandas).
Experience with big data technologies: Apache Spark, Trino/Presto, Parquet, Iceberg, or similar columnar/lakehouse formats.
Experience with Redis (caching, pub/sub, session management) and S3-based storage patterns.
Experience with Agile development methodologies, test-driven development (TDD), and zero-downtime deployment patterns (blue/green, rolling releases).
Prior experience as a Lead / Staff / Principal Engineer or similar leadership role, driving significant technical initiatives across multiple teams.
Familiarity with the business process management, process mining, or workflow automation domains.
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 need a reasonable accommodation during the application or the recruiting process, please submit a request via this Accommodations Request Form .
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