AI Software Engineer (MTS) – Digital Success Engineering

Salesforce•San Francisco, IL

6d•Onsite

About The Position

Salesforce is the #1 AI CRM, where humans with agents drive customer success together. The Digital Success Engineering team within Digital Experience Technology is building Agentforce-powered AI agents that handle customer support inquiries autonomously — resolving routine questions, deflecting cases, and delivering live chat support at scale. As Customer Zero for Agentforce, we are at the absolute bleeding edge of autonomous agent development, pioneering architectural patterns that shape how global enterprises deploy AI. We are looking for an AI Software Engineer (Member of Technical Staff) who thrives in a fast-paced environment, delivers incrementally, and thinks creatively. You will build cutting-edge agent technologies using Agentforce, Agent Script, Salesforce CRM, and Data Cloud.

Requirements

Bachelor’s degree in Computer Science, Software Engineering, or equivalent practical experience.
MTS: 3–5+ years of software engineering experience with strong backend development exposure including demonstrated experience designing and scaling AI/ML services or conversational AI systems.
Strong hands-on proficiency in object-oriented/statically typed languages (Java, Python, Apex, or C#) within microservice, multi-tenant SaaS environments.
Solid understanding of Large Language Models (LLMs), RAG architectures, prompt engineering/optimization, embeddings, and vector databases.
Hands-on experience or working familiarity with the Salesforce Platform (Apex, LWC, Flows, API integrations, Agentforce).
Experience developing and consuming RESTful/GraphQL APIs, managing data pipelines, and working with both relational and non-relational database architectures.
Familiarity with modern developer tools and practices (Git, CI/CD, unit testing frameworks, automated E2E testing).
Excellent problem-solving skills and ability to translate complex technical concepts to non-technical stakeholders in a cross-functional environment.

Nice To Haves

Direct hands-on experience with Salesforce Agentforce, Agent Script, or Data Cloud.
Prior background building customer service bots, autonomous agents, or multi-agent orchestration frameworks at scale.
Deep experience with evaluation techniques for GenAI, including RLHF, bias mitigation, and safety guardrailing.
Salesforce certifications (e.g., Platform App Builder, Salesforce Developer, or AI Associate/Specialist).

Responsibilities

Design, build, and optimize enterprise-grade AI agents using Agentforce Builder, Agent Script, and New Graph Architecture (NGA).
Develop agent topics, reasoning paths, skills, and fallback flows to deliver rich, multi-turn, multilingual support experiences.
Craft, evaluate, and iterate on system prompts, guardrails, and contextual instructions (using techniques like few-shot learning and chain-of-thought) to maximize response accuracy, safety, and operational efficiency.
Build robust integrations connecting AI agents to Salesforce Data Cloud, Apex, REST/GraphQL APIs, and external enterprise systems to fuel agents with real-time context.
Implement testing frameworks, A/B testing, and benchmarking to measure conversation quality, deflection accuracy, hallucination rates, and semantic search precision.
Partner with Product Management, Architects, and AI Researchers to test unreleased Agentforce capabilities internally, feeding critical insights back into core platform product roadmaps.
Participate in agile release cycles, contribute to CI/CD pipelines, conduct code reviews, and join on-call rotations to ensure high availability and sub-second response times for global, multi-tenant operations.