Lead AI Software Engineer

Join a high-velocity team with deep startup roots as a Lead AI Software Engineer on the Agentforce Operations Process Generation Team. You will drive the ongoing development of intelligent agents that capture how a customer runs their business today, propose improvements, and turn the result into an executable blueprint of agent and human tasks.

Drive Agent Development & Architecture

• Lead development of intelligent agents that complete complex supply chain tasks with reliability and consistency
• 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

Lead Technical Strategy

• Partner with Product Management and Executive Leadership to translate business vision into multi-year technical roadmaps
• Guide technical decision-making for AI model deployment, safety constraints, and reliability frameworks
• Drive adoption of enterprise-grade observability tools and cloud infrastructure best practices

Mentor & Collaborate

• Mentor engineers to improve code quality, AI/ML practices, and system design
• Collaborate with cross-functional teams including Design, Product Management, and industry experts to build high-quality product features
• Take on new challenges and responsibilities as needed, and be an enthusiastic team player in a dynamic environment
• Engage directly with customers to gather insights and validate technical approaches
• Participate in hiring decisions and contribute to our culture of continuous learning

Requirements

• B.S. in Computer Science or equivalent with coursework in Artificial Intelligence (M.S. preferred)
• 5+ years of industry experience in Software Engineering, with a focus in AI/ML
• Proficiency in multiple programming languages such as Python, Go, Java, or C++
• Strong background in APIs, data modeling, and databases
• Demonstrated ability to work both independently and collaboratively in a dynamic environment
• Expertise in model evaluation, with a track record of designing custom benchmarks and automated testing suites for complex models

Nice to Have

• Understanding of current LLM orchestration frameworks and experience moving past them when necessary
• Passion for continuous learning and development in AI technologies, and enthusiasm for mentoring peers
• Proven collaborator who can manage stakeholders and drive consensus across diverse engineering and product teams
• Experience with enterprise-grade observability tools (e.g., Splunk) and cloud infrastructure (AWS/GCP)

The typical base salary range for this position is $172,500 - $260,100 annually. In select cities within the San Francisco and New York City metropolitan area, the base salary range for this role is $207,800 - $285,800 annually.