Salesforce

1 month ago

Lead AI Engineer, Data Solutions

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 1 day agoStatus: Live

Job Summary

Lead AI Engineer to design and deploy next-generation AI/ML systems at Salesforce, focusing on intelligent decisioning, agent flywheel feedback loops, and data pipelines that enable continuous learning in production. You will build models and agents, own data and model pipelines, evaluation loops, and integration with business workflows to continuously improve agent performance, engagement, and revenue impact across enterprise CRM platforms.

Location: San Francisco

Workplace: Hybrid

Employment Type: Full time

Job Function: Data Science & Machine Learning

Seniority: Manager level

Key Responsibilities

•Design and implement the Agent Flywheel, including feedback loops to improve from real-world outcomes and tracking engagement, conversion, and quality metrics
•Develop ML and agent systems by building and deploying models (classification, ranking, forecasting, recommendation) and designing AI agents that combine LLM reasoning, tool usage, and ML decisioning
•Own data and model pipelines by designing scalable batch and near real-time data pipelines for training, evaluation, and inference, and enabling continuous retraining
•Create evaluation frameworks (offline/online), datasets, and experimentation processes (A/B testing, regression tests) to drive continuous optimization
•Develop systems and APIs powering agent workflows, ensure reliability, observability, and performance across production environments

Pay and Benefits

Salary: USD 172,500 - 260,100 annually

Equity and Bonus:Equity

Perks:401kEquity

Key Requirements

•6+ years in AI/ML engineering or applied data science
•Strong Python experience in production systems and proven experience building and deploying ML models
•Experience building data pipelines (ETL/ELT, batch or streaming) and APIs/backend systems
•Experience with LLM-powered systems (prompting, orchestration, evaluation) and familiarity with agent workflows
•Experience with Spark, Airflow/Dagster, Snowflake/BigQuery; understanding of data quality, lineage, and reproducibility

Experience:6+ yearsAIMLData pipelinesEnterprise software

Skills:CommunicationProblem-solvingTeamworkLeadershipCollaboration

Tech Stack:PythonSparkAirflowDagsterSnowflakeBigQueryLLMsAPIsML

Company Brief

Salesforce

Provides a leading cloud-based customer relationship management (CRM) platform with sales, service, marketing, analytics, and integration tools that empower businesses to manage customer relationships and digital transformation at scale.

Industry: SaaS

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: San Francisco, United States

Founded: 1999

Glassdoor: 4.1

Website LinkedIn Glassdoor

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Salesforce

1 month ago

Lead AI Engineer, Data Solutions

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 1 day agoStatus: Live

Job Summary

Location: San Francisco

Workplace: Hybrid

Employment Type: Full time

Job Function: Data Science & Machine Learning

Seniority: Manager level

Key Responsibilities

•Design and implement the Agent Flywheel, including feedback loops to improve from real-world outcomes and tracking engagement, conversion, and quality metrics
•Develop ML and agent systems by building and deploying models (classification, ranking, forecasting, recommendation) and designing AI agents that combine LLM reasoning, tool usage, and ML decisioning
•Own data and model pipelines by designing scalable batch and near real-time data pipelines for training, evaluation, and inference, and enabling continuous retraining
•Create evaluation frameworks (offline/online), datasets, and experimentation processes (A/B testing, regression tests) to drive continuous optimization
•Develop systems and APIs powering agent workflows, ensure reliability, observability, and performance across production environments

Pay and Benefits

Salary: USD 172,500 - 260,100 annually

Equity and Bonus:Equity

Perks:401kEquity

Key Requirements

•6+ years in AI/ML engineering or applied data science
•Strong Python experience in production systems and proven experience building and deploying ML models
•Experience building data pipelines (ETL/ELT, batch or streaming) and APIs/backend systems
•Experience with LLM-powered systems (prompting, orchestration, evaluation) and familiarity with agent workflows
•Experience with Spark, Airflow/Dagster, Snowflake/BigQuery; understanding of data quality, lineage, and reproducibility

Experience:6+ yearsAIMLData pipelinesEnterprise software

Skills:CommunicationProblem-solvingTeamworkLeadershipCollaboration

Tech Stack:PythonSparkAirflowDagsterSnowflakeBigQueryLLMsAPIsML

Company Brief

Salesforce

Industry: SaaS

Company Size: Enterprise (1,001+ employees)

Revenue: USD 1B+

Growth: Public Company

Valuation: Public Company (Market Cap in USD)

Funding: IPO / Publicly Listed

Headquarters: San Francisco, United States

Founded: 1999

Glassdoor: 4.1

Website LinkedIn Glassdoor