Salesforce
AI CRM
LeadAIEngineer
“Lead AI Engineer at Salesforce. Skills: AI/ML Engineering, Agent Systems, Data Pipelines, LLM Systems. Build the Agent Flywheel. Design feedback loops”
What You'll Achieve.
Agents and ML models measurably improve over time; Well-structured data and evaluation pipelines continuously feeding the agent flywheel; Clear lift in key business metrics; Robust evaluation systems enabling rapid iteration and safe deployment; Improve agent performance, efficiency, revenue, and customer experience
Industry & Context.
intelligent decisioning systems; self-improving feedback loops; self-improving systems
What They're Looking For.
Must Have
6+ years of experience in AI/ML engineering, applied data science, or closely related roles, hands-on experience in Python for production systems, Proven track record building and deploying production-grade ML models, experience with data pipeline development (ETL/ELT, batch or streaming), Experience designing and building AI agents or agent-like systems, experience with API development and backend services, Experience with ML lifecycle tooling (training, evaluation, deployment, monitoring), Experience building reliable data pipelines that support ML or AI systems in production, Experience building or working with LLM-powered systems (prompting, orchestration, evaluation), Strong understanding of supervised learning (classification, regression, ranking), Strong understanding of evaluation methodologies (offline + online), Strong understanding of experimentation (A testing, causal inference basics), Ability to design systems that combine ML models, LLMs, and business logic, Experience deploying models/services in production environments, Ability to write clean, scalable, maintainable code
Nice to Have
Experience building model-driven agent improvement systems (e.g., scoring, gating, auto-optimization), Experience with reinforcement learning, bandits, or iterative optimization systems, Exposure to agent evaluation tools (e.g., LangSmith, Braintrust, or similar concepts), Experience with large-scale experimentation platforms, Familiarity with enterprise SaaS or CRM domains, Experience working with agent traces, evaluation datasets, or iterative improvement loops
What You'll Do.
Build the Agent Flywheel
Design feedback loops
Develop outcome tracking systems
Develop agent evaluation systems
Develop iterative optimization systems
Build data collection pipelines
Close loop from production signals
Develop Production ML & Agent Systems
Build and deploy ML models
Design and implement AI agents
Implement reusable agent patterns
Integrate ML and agent capabilities
Data & Pipeline Engineering
Design and build scalable data pipelines
Develop feature and label pipelines
Partner model and data pipelines
Work with large-scale data
Experimentation & Optimization
Build evaluation frameworks
Develop evaluation datasets
Design and run A experiments
Define and monitor key metrics
Drive continuous optimization
Architecture & Applied Systems Design
Develop hybrid systems
Collaborate with platform teams
Design scalable systems
Platform & API Development
Build scalable Python services
Contribute to shared infrastructure
Ensure system reliability
How You'll Work.
Team & Collaboration
Collaborate with platform teams
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