AI Software Engineer MTS
Buenos Aires | Hybrid

JOB DESCRIPTION

The AI Solutions team in Technology & Product builds the products and platforms that help Salesforce engineers use AI coding tools safely, effectively, and measurably. Our work spans DevBar, AI usage telemetry, code attribution, budget governance, developer intelligence, and the integrations that make AI tools easier to adopt at Salesforce scale.

As a Member of Technical Staff, you will build and operate full-stack product and platform capabilities across desktop applications, backend services, data pipelines, dashboards, and developer-facing integrations. Working with experienced engineers and product partners, you will turn product needs into reliable software, own well-defined areas end to end, and help thousands of Salesforce engineers get more value from AI every day.

What You'll Actually Be Doing

• Design, implement, test, and ship full-stack features across AI Solutions products, including DevBar, AI metrics, AI attribution, budget governance, and related developer intelligence surfaces.

• Build backend APIs, data models, ingestion flows, dashboards, and user experiences that connect AI tool usage to outcomes engineers and leaders can act on.

• Contribute to technical designs and turn product requirements into clear, incremental implementation plans with support from senior engineers when needed.

• Own features and services in production by improving observability, reliability, performance, security, and supportability as part of the software development lifecycle.

• Build and ship high-quality, production-grade software using modern engineering practices, with AI as a core part of your development workflow to deliver secure, optimized, and maintainable code.

• Build AI-enabled and agentic workflows that fit naturally into how developers work, with appropriate evaluation, safeguards, and human oversight.

• Contribute to shared system context - designs, constraints, standards, and operational knowledge - that helps both people and AI agents work accurately and reliably.

• Review human- and AI-generated code for correctness, quality, security, and performance; participate actively in design and code reviews; and share what you learn with the team.

You're Our Person If...

• 3+ years of professional experience building production software, including full-stack applications, backend services, developer tools, or internal platforms.

• Strong programming fundamentals and proficiency in at least one modern language, with the ability to work across frontend, backend, APIs, data stores, and service boundaries.

• Experience delivering well-defined features through design, implementation, testing, rollout, and production ownership.

• A practical understanding of data structures, API design, automated testing, source control, CI/CD, and secure software development practices.

• Ability to debug technical issues, use logs and metrics to understand system behavior, and make thoughtful tradeoffs with guidance when appropriate.

• Clear communication and collaboration skills, including the ability to ask good questions, give and receive feedback, and work effectively with engineers and product partners.

• A demonstrated AI-first approach to engineering - using tools such as Claude Code, GitHub Copilot, Codex, or Cursor to move faster while validating outputs and maintaining quality.

• The ability to write precise, structured prompts and contribute the context, examples, and constraints that make AI-assisted development reliable and production-ready.

• A related technical degree is required.

Even Better If...

• Experience building developer tools, AI coding tool integrations, internal platforms, telemetry systems, or enterprise desktop applications.

• Familiarity with React, TypeScript, Go, service APIs, event pipelines, analytics systems, or cloud- and Kubernetes-based services.

• Experience building self-service experiences, dashboards, plugin systems, command-line tools, or reusable integration patterns for engineering teams.

• Hands-on experience with LLM applications, agentic workflows, prompt evaluation, or safety and quality controls for AI-enabled features.

• Interest in AI developer productivity and helping engineering teams adopt AI tools in ways that are measurable, trustworthy, and scalable.