Senior AI Engineer, Salesforce

• 3+ years of industry experience building production AI systems and/or backend services
• Bachelor's or Master's degree in Computer Science, Software Engineering, or a related STEM field with strong competencies in algorithms, data structures, and software design
• Strong Python programming skills; experience building production-grade async services (FastAPI or equivalent)
• Experience with distributed, scalable systems and modern data storage frameworks such as Redis, Kafka, and Docker/Kubernetes
• Experience integrating with LLMs and prompt engineering in production systems
• Proven ability to innovate and deliver results at scale

Desirable

• Salesforce is looking for an AI Software Engineer to be part of the team building and scaling the Agentforce Reasoning Engine — the core Python/FastAPI service powering multi-agent orchestration in Agentforce
• You will work on the infrastructure and AI systems that enable intelligent agents to reason, plan, and act on behalf of millions of customers every day
• The Team We are a group of Generative AI Application Engineers passionate about designing and building the reasoning backbone of Agentforce
• We love to learn, teach, and help each other, and we seek individuals with a collaborative attitude and openness to others' ideas
• You will play a critical role in building and scaling the Agentforce Reasoning Engine — a Python/FastAPI service that orchestrates multi-agent workflows and integrates with LLM backends
• You will own scalable backend services that handle session state, agent coordination, and LLM call chains across thousands of concurrent tenants
• You will collaborate with AI Platform Engineers and Software Engineers to define requirements, improve reliability, and ship production AI systems
• Build and own end-to-end scalable backend services powering multi-agent orchestration, supporting thousands of tenants at production scale
• Design and improve stateful session management using Redis and distributed storage patterns
• Drive system efficiencies through automation, including capacity planning, performance tuning, monitoring, and root cause analysis
• Participate in periodic on-call rotations and be available to resolve critical issues
• Collaborate with Product Managers, Application Architects, and AI researchers to bring innovative agent reasoning capabilities to production