Lead Software Engineer, AI Workflow Generation (Agentforce Operations)

Salesforce•San Francisco, CA

6d•$172,500 - $285,800

About The Position

Salesforce is hiring a Lead Software Engineer for the Agentforce Operations Process Generation Team. The team builds agents that capture how customers run their businesses, propose improvements, and turn the resulting processes into executable blueprints of agent and human tasks. These agents plan and execute multi-step work to deliver consistency, correctness, and automation at scale. The role is part of a high-velocity startup-within-Salesforce, backed by Salesforce Data Cloud and security infrastructure. The team is developing a 0-to-1 product for automating end-to-end business processes, initially addressing supply chains and collaboration through channels such as email. The Lead Engineer will lead agent development and architecture, shape technical strategy, mentor engineers, collaborate with cross-functional partners, and engage directly with customers. The work includes building reliable intelligent agents and distributed systems, designing autonomous planning systems, guiding AI model deployment and safety, and improving observability and cloud infrastructure practices.

Requirements

Bachelor’s degree in Computer Science or equivalent, with coursework in Artificial Intelligence; a master’s degree is preferred.
5+ years of industry experience in Software Engineering focused on AI/ML; the posting specifies 7–12 years for Lead roles and 4–8 years for Senior roles.
Proficiency in multiple programming languages, such as Python, Go, Java, or C++.
Strong background in APIs, data modeling, and databases.
Ability to work independently and collaboratively in a dynamic environment.
Expertise in model evaluation, including a track record of designing custom benchmarks and automated testing suites for complex models.
Experience integrating production telemetry to monitor live model performance and data drift.

Nice To Haves

Understanding of current LLM orchestration frameworks and experience moving beyond them when necessary.
Passion for continuous learning and development in AI technologies, and enthusiasm for mentoring peers.
Ability to collaborate, manage stakeholders, and drive consensus across diverse engineering and product teams.
Experience with enterprise-grade observability tools such as Splunk and cloud infrastructure such as AWS or GCP.

Responsibilities

Lead development of intelligent agents that complete complex supply chain tasks reliably and consistently.
Spearhead architectural decisions for distributed systems serving millions of users with 24/7 availability.
Design and implement planning systems that enable agents to execute multi-step workflows autonomously.
Partner with Product Management and Executive Leadership to translate business vision into multi-year technical roadmaps.
Guide technical decisions for AI model deployment, safety constraints, and reliability frameworks.
Drive adoption of enterprise-grade observability tools and cloud infrastructure best practices.
Mentor engineers to improve code quality, AI/ML practices, and system design.
Collaborate with Design, Product Management, and industry experts to build product features.
Take on new challenges and responsibilities as needed and contribute as a team player in a dynamic environment.
Engage directly with customers to gather insights and validate technical approaches.
Participate in hiring decisions and contribute to a culture of continuous learning.