* Use Claude Code (CLI) as a primary engineering tool writing, refactoring, debugging, and reviewing infrastructure and platform code with AI pair programming as the default, not the exception.* Build and publish reusable AI tools, skills, and integrations in internal tool marketplaces so that platform capabilities are discoverable and reusable across engineering teams.* Design and deploy autonomous agents that accelerate developer workflows, self-healing CI pipelines, automated onboarding bots, infrastructure diagnosis agents, and documentation generation.* Author and maintain CLAUDE.md files across platform repos, encoding platform conventions, deployment patterns, and team knowledge so that AI tools produce high-quality, context-aware output from day one.* Define and enforce AI-first engineering standards across the team: how engineers prompt, how context is managed, how agent output is reviewed before it ships.* Design, implement, and manage secure and scalable cloud infrastructure (primarily AWS) including IAM permissions management, data management, and Kubernetes.* Leverage AI tooling (Claude Code, autonomous agents) to accelerate infrastructure-as-code authoring, drift detection, and security review reducing manual toil on repeatable tasks.* Build and curate an internal AI tool and skills marketplace where engineers can discover, reuse, and extend trusted integrations connecting AI agents to platform data sources, APIs, and services via MCP servers.* Develop internal developer tools (web interfaces, AI assistants, CLI tools) that let ML engineers and data scientists self-serve without platform team involvement.* Implement secrets management, package/dependency management, testing frameworks, and observability integrations and use AI tooling to keep these maintained and documented at scale.* Participate in security reviews and ensure all platform components including AI tooling and agent infrastructure adhere to security best practices and compliance requirements.* Own the security posture of AI tool integrations: sandboxed execution, auditable agent traces, least-privilege tool permissions.* 9+ years of proven experience as a Platform Engineer, Software Engineer, or ML Infrastructure Engineer.* Demonstrated AI-native engineering practice, you actively use tools like Claude Code (CLI), Cursor, or equivalent AI pair programmers as part of your daily engineering workflow; this is visible in your work, not aspirational.* Experience building or contributing to an internal tool or skills marketplace publishing reusable integrations, MCP servers, or AI building blocks that other teams depend on.* Experience designing and deploying autonomous agents that perform real engineering tasks: CI diagnosis, infrastructure ops, developer onboarding, documentation generation.* Strong software engineering skills in Python for building scalable tools, automation scripts, and platform components.* Experience with MCP (Model Context Protocol) servers building, hosting, and securing tool integrations for AI agents.* Strong expertise in AWS (IAM, EKS, S3, SageMaker, Lambda, etc.).* Extensive experience with CI/CD tools, especially GitHub Actions and ArgoCD.* Proficiency in infrastructure-as-code (Terraform).* Experience with containerization (Docker) and orchestration (Kubernetes).* Experience with MLOps concepts and tools.* Experience with model and agent evaluation.* Familiarity with monitoring and alerting systems (Grafana, PagerDuty).* Familiarity with Okta or similar IAM systems.* Experience with tenant and project onboarding in multi-tenant environments.* Familiarity with security best practices and conducting security reviews.* Experience developing internal developer tools (web, AI assistants, CLIs).* Ability to manage multiple priorities; excellent problem-solving and communication skills.* Experience with the Salesforce ecosystem.* Familiarity with agent memory patterns: context management, long-term retrieval, episodic memory.* Experience with unstructured databases (vector or graph) and RAG pipelines.* Experience with modern data platforms: Snowflake, Kafka, Flink.* Experience with Feature Stores (e.g., Feast).* Experience with A/B testing and experimentation platforms.* Knowledge of Airflow or other workflow orchestration tools.When you join Salesforce, you’ll be limitless in all areas of your life. Our benefits and resources support you to find balance and *be your best*, and our AI agents accelerate your impact so you can *do your best*. Together, we’ll bring the power of Agentforce to organizations of all sizes and deliver amazing experiences that customers love. Apply today to not only shape the future — but to redefine what’s possible — for yourself, for AI, and the world.Please note that Salesforce uses artificial intelligence (AI) tools to help our recruiters assess and evaluate candidates’ resumes and qualifications throughout the recruiting process. Humans will always make any candidate selection and hiring decisions. Please see our for more information about how we use your personal data and your rights, including with regard to use of AI tools and opt out options.Any employee or potential employee will be assessed on the basis of merit, competence and qualifications – without regard to race, religion, color, national origin, sex, sexual orientation, gender expression or identity, transgender status, age, disability, veteran or marital status, political viewpoint, or other classifications protected by law. This policy applies to current and prospective employees, no matter where they are in their Salesforce employment journey. It also applies to recruiting, hiring, job assignment, compensation, promotion, benefits, training, assessment of job performance, discipline, termination, and everything in between. Recruiting, hiring, and promotion decisions at Salesforce are fair and based on merit. The same goes for compensation, benefits, promotions, transfers, reduction in workforce, recall, training, and education.#J-18808-Ljbffr