Salesforce

1 month ago

Principal AI Engineer

✓ Verified Job

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

Source: Company careers pageValidated by: Fursa AI

Last checked: 23 hours agoStatus: Live

Job Summary

Lead the design and development of the ML/AI platform powering autonomous AI agents at enterprise scale. Build agent harnesses, sandboxed execution environments, evaluation frameworks, and end-to-end lifecycle tooling, delivering scalable, secure, and observable platform services used across marketing, sales, service, and product growth.

Location: Mexico City

Workplace: Hybrid

Employment Type: Full time

Job Function: Data Science & Machine Learning

Key Responsibilities

•Design and build agent harness infrastructure: the scaffolding that wraps LLM calls, manages tool use, handles retries, enforces policy, and feeds results back into iterative improvement loops
•Implement agentic loop patterns with multi-turn reasoning, tool orchestration, memory management, and structured output handling as reusable platform primitives
•Build the agent flywheel: automated pipelines that collect agent traces, surface regressions, route failures to evaluation, and close the loop from production signal back to prompt/model improvement
•Own the end-to-end lifecycle from agent experiment to production deployment, including versioning, rollout controls, and rollback mechanisms
•Build sandboxed execution environments for agent tools with isolating code execution, API calls, and file system access so agents can act without unconstrained blast radius

Key Requirements

•9+ years as a Platform Engineer, ML Infrastructure Engineer, or Software Engineer
•Demonstrated experience building agent harness infrastructure using agentic loops, tool orchestration, structured output handling, multi-turn conversation management
•Hands-on experience with agent evaluation frameworks like Braintrust, LangSmith, or equivalent, including building eval datasets, running automated regression suites, and tracking quality metrics over time
•Strong understanding of sandboxing and safe agent execution like isolation patterns, tiered autonomy, blast radius controls
•Experience with context Engineering as it relates to Agent orchestration

Experience:9+ yearsAISaaSEnterprise softwareML infrastructurePlatform engineering

Skills:PythonAWSGitHub ActionsArgoCDTerraformDockerKubernetesGrafanaPagerDuty

Tech Stack:PythonAWSGitHub ActionsArgoCDTerraformDockerKubernetesGrafanaPagerDuty

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

Principal AI Engineer

✓ Verified Job

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

Source: Company careers pageValidated by: Fursa AI

Last checked: 23 hours agoStatus: Live

Job Summary

Location: Mexico City

Workplace: Hybrid

Employment Type: Full time

Job Function: Data Science & Machine Learning

Key Responsibilities

•Design and build agent harness infrastructure: the scaffolding that wraps LLM calls, manages tool use, handles retries, enforces policy, and feeds results back into iterative improvement loops
•Implement agentic loop patterns with multi-turn reasoning, tool orchestration, memory management, and structured output handling as reusable platform primitives
•Build the agent flywheel: automated pipelines that collect agent traces, surface regressions, route failures to evaluation, and close the loop from production signal back to prompt/model improvement
•Own the end-to-end lifecycle from agent experiment to production deployment, including versioning, rollout controls, and rollback mechanisms
•Build sandboxed execution environments for agent tools with isolating code execution, API calls, and file system access so agents can act without unconstrained blast radius

Key Requirements

•9+ years as a Platform Engineer, ML Infrastructure Engineer, or Software Engineer
•Demonstrated experience building agent harness infrastructure using agentic loops, tool orchestration, structured output handling, multi-turn conversation management
•Hands-on experience with agent evaluation frameworks like Braintrust, LangSmith, or equivalent, including building eval datasets, running automated regression suites, and tracking quality metrics over time
•Strong understanding of sandboxing and safe agent execution like isolation patterns, tiered autonomy, blast radius controls
•Experience with context Engineering as it relates to Agent orchestration

Experience:9+ yearsAISaaSEnterprise softwareML infrastructurePlatform engineering

Skills:PythonAWSGitHub ActionsArgoCDTerraformDockerKubernetesGrafanaPagerDuty

Tech Stack:PythonAWSGitHub ActionsArgoCDTerraformDockerKubernetesGrafanaPagerDuty

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