Senior/Lead/Principal Software Engineer, Agentforce Operations

salesforce.com, inc.; Seattle (WA); On-site; USD 148,500 - 313,700; Full time

Job summary

Salesforce seeks a senior backend engineer to shape the Agentforce Operations platform. You will architect and build the integration backbone, optimize data pipelines, and deliver scalable APIs that connect to MuleSoft, Flow, and Data Cloud.

You’ll own cross-team interfaces and guide system design with an AI-first approach. You’ll work on high-impact backend challenges, decompose complex domains, and mentor engineers while collaborating with Product Managers to deliver enterprise-grade

Qualifications

• 3+ years (Senior), 5+ years (Lead), 8+ years (Principal) of backend engineering experience.
• Related technical degree required.
• Expert in data modeling, DB performance tuning, state management, API design, concurrency, fault tolerance, and scaling.
• Proven experience designing and maintaining production-grade data pipelines (ETL/ELT).
• Expertise in at least one modern language (Java, Python, Go).
• Experience designing/maintaining robust REST APIs and Webhooks.
• Deep knowledge of distributed systems and high-availability architectures.
• Experience leading technical initiatives as a senior engineer or lead.
• Strong collaboration with Product Managers and other teams.
• Familiarity with Salesforce integration technologies (MuleSoft, Data Cloud).

Responsibilities

• Architect and implement integrations between core platform and Salesforce ecosystem products.
• Lead scalable, reliable data export pipelines; integrate internal data sources with Data Cloud or Informatica.
• Optimize ETL pipelines to support daily self-serve data synchronization.
• Design and build efficient, customer-facing APIs and webhooks, including GraphQL endpoint abstractions.
• Architect and deliver high-quality, scalable code for data integration and platform features.
• Drive technical decision-making and project execution as a primary contributor.
• Perform thorough code reviews and mentor engineers on performance, security, and scalability.
• Collaborate with Product Management and other teams to define requirements and solutions.
• Build and ship production-grade software with AI as a core development factor.
• Design systems to enable AI agents to operate within human workflows.
• Contribute to shared system context of designs, constraints and standards.
• Critically evaluate code for correctness, quality, security, and performance.
• Lead by example and raise engineering quality bars across teams.
• Set technical direction for data integration, ETL, and backend architecture.
• Identify architectural risks and drive scalability improvements.
• Improve system performance, observability, and operability.

Skills

Backend engineering

Data modeling

API design

Distributed systems

DB performance tuning

REST APIs

GraphQL

AI-first engineering

Mentoring engineers

Programming languages

Education

Bachelor's degree in CS or related

Tools

MuleSoft

Flow

Data Cloud

REST

GraphQL

Kubernetes

Docker

Job description

Software Engineering

The Experience

Global supply chains still rely on slow, manual processes—email, spreadsheets, and fragmented data. The economy moves fast but supply chains don't, creating an inefficiency that affects the $13T of goods shipped annually and is one of the largest untapped opportunities in modern enterprise. Agentforce Operations is reimagining the supply chain with an AI-powered platform for designing, automating, and running end-to-end business processes, with seamless collaboration through familiar channels like email. For Salesforce, this represents a massive growth opportunity in the back office, with innovations that flow into the front office.

Super Agent Team

Super Agent backend is the operational heart of Agentforce Operations—managing complex, infinitely configurable state with equally complex state transitions and interfaces across the platform. Built with intentional startup speed, the team is now hardening and scaling its foundations as customer adoption accelerates. You’ll work on one of the most technically challenging and impactful backends at Salesforce: decomposing tightly coupled domains, hardening state transitions, designing cross‑team boundaries, and building the observability needed to operate confidently at enterprise scale. Wide autonomy, real ownership and meaningful advancement await.

Integration & Platform Team

The Integration & Platform team owns the mission‑critical data and integration backbone of the Agentforce Operations. They design, build, and scale the systems that connect our platform to the broader Salesforce ecosystem—including MuleSoft, Flow, and Data Cloud—while also powering the self‑serve data synchronization mechanisms that customers depend on daily. Their work directly forms the foundational data layer enabling core customer intelligence, platform functionality, and enterprise‑grade reliability at scale.

What You’ll Actually Be Doing

Super Agent

• Diagnose and prioritize the most impactful foundational investments across the Super Agent backend, partnering with engineering leadership to sequence them against product delivery.
• Own the hardest cross‑cutting system problems, from architectural decomposition to cross‑team interface design, going deep hands‑on when the problem demands it.
• Build shared understanding of system health and risk across the team, helping establish frameworks and observability needed to make investment decisions with confidence.
• Raise and maintain the engineering quality bar through pragmatic standards, guardrails, and team practices that prevent regressions and keep code healthy over time.

Integration & Platform

• Architect and implement powerful integrations between the core platform and Salesforce ecosystem products, specifically MuleSoft and Flow.
• Lead the design and implementation of highly scalable, efficient, and reliable data export pipelines, integrating internal data sources (CSV files, REST API outputs) with Salesforce Data Cloud and/or Informatica.
• Optimize existing ETL pipeline infrastructure to support a daily, self‑serve customer data synchronization mechanism with Data Cloud—fully automated, requiring minimal engineering involvement post‑setup.
• Design and build simplified, performant, customer‑facing APIs and webhooks, including an abstracted version of high‑value functionality currently exposed via complex GraphQL endpoints.

Shared Responsibilities

• Architect, design, and deliver high‑quality, scalable code for complex data integration and platform features.
• Drive technical decision‑making and project execution as the primary individual contributor for key initiatives.
• Conduct thorough code reviews and mentor engineers on best practices for performance, security, and scalability.
• Collaborate cross‑functionally with Product Management and other engineering teams to define requirements and deliver solutions that meet business needs.
• Build and ship production‑grade software using modern engineering practices, with AI as a core part of your development workflow.
• Design and orchestrate complex systems where AI agents integrate seamlessly into human workflows.
• Contribute to building and maintaining shared system context—an explicit repository of system designs, constraints, and standards that enables AI to operate accurately and reliably.
• Critically evaluate code (human or AI‑generated) for correctness, quality, security, and performance.
• Mentor engineers as a senior peer and force multiplier, helping shape stronger engineering judgment and a higher‑performing team.

Long‑Term Strategic Impact

• Set the technical direction and standards for data integration, ETL processes, and backend architecture across the platform.
• Identify and mitigate architectural risks associated with scaling our data infrastructure to support exponential customer growth.
• Drive continuous improvement in system performance, observability, and operational efficiency.

You’re Our Person If …

• 3+ years (Senior), 5+ years (Lead), 8+ years (Principal) of industry experience as a backend engineer, building and operating large‑scale, user‑facing web applications and/or data systems.
• A related technical degree required.
• Deep expertise in multiple areas of backend engineering: data modeling, DB performance tuning, state management, API design, transactionality, concurrency, fault tolerance, and scaling.
• Demonstrated expertise in designing, building, and maintaining production‑grade data pipelines (ETL/ELT).
• Expert‑level proficiency in at least one modern programming language (e.g., Java, Python, Go) suitable for platform development.
• Proven experience designing and implementing robust, external‑facing REST APIs and Webhooks.
• Deep practical knowledge of distributed systems, high‑availability architectures, event queues, and asynchronous task processing.
• Track record of diagnosing systemic architectural problems, prioritizing across competing technical investments, and driving measurable improvement over time.
• Experience designing and improving interfaces and boundaries between teams and systems.
• Experience in a lead technical role (LMTS/PMTS level or equivalent), driving and owning complex projects as an individual contributor.
• Excellent written and verbal communication skills, with the ability to lead real‑time technical design discussions.
• Experience working in tandem with Product Managers and Engineers to shape requirements, evaluate tradeoffs, and balance product delivery against foundational investment.
• Demonstrated ownership and accountability, with a consistent track record of high standards and low‑ego collaboration.
• A demonstrated, genuine AI‑first approach to engineering—using AI to move faster, build fluency across the stack, and contribute well beyond your core specialty.
• Experience using AI tools (e.g., Claude Code, GitHub Copilot, Codex, Cursor, etc.) in development workflows.
• Advanced prompt engineering skills and the ability to write precise, structured prompts and cultivate system context that makes AI outputs reliable, secure, and production‑ready.

Even Better If …

• B.S. in Computer Science (M.S. preferred).
• Mastery of Golang, GraphQL, and PostgreSQL.
• Hands‑on experience with Salesforce integration technologies such as MuleSoft or Salesforce Data Cloud.
• Experience working with large‑scale event streaming platforms (e.g., Kafka, Kinesis).
• Familiarity with containerization and orchestration technologies (e.g., Docker, Kubernetes).
• Experience designing or working with GraphQL API implementations.
• Experience with workflow engines.
• Exposure to the supply chain, logistics, or manufacturing industry.
• Experience working within rapidly evolving systems, balancing early‑stage ambiguity with scaling, reliability, and maintainability concerns.
• Notable open‑source contributions, patents, or published research.
• Familiarity with the Salesforce platform.

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.

Accommodations

If you need a reasonable accommodation during the application or the recruiting process, 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. 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.

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. 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. At Salesforce, we believe in equitable compensation practices that reflect the dynamic nature of labor markets across various regions. The typical base salary range for this position is $148,500 - $313,700 annually. In select cities within the San Francisco and New York City metropolitan area, the base salary range for this role is $178,900 - $344,700 annually. The range represents base salary only, and does not include company bonus, incentive for sales roles, equity or benefits, as applicable.