Lead Software Engineer (AI/ML)

Salesforce•Seattle, WA

3d•$172,500 - $260,100•Onsite

About The Position

Salesforce is seeking an enthusiastic Lead Engineer with an AI-first approach to build and maintain code validation, ensuring production readiness for customers. This role involves working on SPIFF, a Sales rep compensation engine, and translating traditional testing to AI-driven acceleration and accuracy. The engineer will collaborate with cross-functional teams, including product development, data science, and AI teams, to ensure Salesforce’s AI-driven solutions meet the highest quality standards for enterprise applications. The position emphasizes integrating cutting-edge AI technologies into software engineering workflows.

Requirements

10+ years of experience of proven software development experience
Strong JAVA skills: Strong technical fundamentals of Java particularly in data structures and algorithms.
Ability to code and evaluate code written by AI agents and provide feedback to scale internal models to improve code quality.
Familiarity with LLM and AI/ML techniques and practices to drive software validation and improve the pace of CICD pipelines.
Focus on Delivery: Ability to deliver practical solutions for an active user base, with follow-up enhancements and improvements as needed.
Excellent communication skills, with the ability to work cross-functionally with product managers, engineers, AI/ML engineers, and data scientists.
Strong analytical and problem-solving abilities with a focus on identifying quality gaps and driving improvement.
A demonstrated, genuine AI-first approach to engineering.
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 the system context that makes AI outputs reliable, secure, and production-ready.
A related technical degree required.

Nice To Haves

Prior experience as a member of a Data Science, ML Science, or ML Engineering team is a plus.
Hands-on experience evaluating Large Language Models (LLMs) for quality response, including familiarity with GPT-like models and AI evaluation frameworks is a big plus.
A software engineer with strong coding background and understanding of delivering software at pace in Agentic PDLC.
A strong experience of white boxing and fixing code is a huge plus.
Strong understanding of public cloud infrastructure - AWS/Azure/GCP.
Certification in Salesforce.
Can design, implement, test and deliver AI/ML-based validation frameworks for highly scalable products.
Fluent with automation technologies such as JUnit, Jest, Selenium and Jenkins.

Responsibilities

Identify opportunities for integrating AI/ML solutions into existing workflows and propose new ones that are high-quality and efficient.
Positively influence engineering decision-making by communicating and evaluating solution options, and facilitating agreement among key stakeholders.
Ensure continuous improvement in engineering excellence and production of high business impact.
Stay informed about developments in AI/ML by tracking publicly available models, frameworks, libraries, and publications, focusing on practical application and relevance to Salesforce.
Provide technical leadership on proof of concepts and influence the direction of R&D.
Demonstrate industry-expert level understanding of quality concerns and validation techniques.
Drive behaviors and initiatives that focus on both quality and throughput.
Oversee human evaluation processes for subjective quality dimensions, such as response engagement, user safety, and contextual accuracy.
Develop and implement robust quality strategies for Salesforce’s SaaS products, focusing on AI/ML and LLM integrations.
Provide technical leadership for critical areas that significantly impact customer success, acting as a consultant on design and delivery of new solutions.
Introduce new best practices to R&D and ensure their adoption.
Deepen and widen understanding of the application and drive discussions on complex or controversial issues in open forums.
Utilize understanding of customers’ needs across industries and multiple technology landscapes to develop solutions across Salesforce's technology stack.
Work in a consultative fashion to improve communication, teamwork, and alignment among teams.
Mentor and develop the expertise and leadership contributions of senior engineers.
Build and ship high-quality, production-grade software using modern engineering practices, with AI as a core part of the development workflow.
Push the boundaries of AI development tools to deliver secure, optimized, and high-quality code.
Design and orchestrate complex systems where AI agents integrate seamlessly into human workflows.
Critically evaluate code (Human or AI-generated) for correctness, quality, security, and performance.
Contribute to building and maintaining the shared system context, an explicit repository of system designs, constraints, and standards that enables AI to operate accurately and reliably.