Principal Architect

Salesforce•Palo Alto, CA

11d•$257,500 - $496,400•Remote

About The Position

Salesforce is seeking a Principal Architect to serve as the visionary anchor for our AI-native engineering organization. This role requires a systems architect and system thinker who understands the intersection of LLM capabilities, cognitive architectures, and enterprise-grade software engineering. The Principal Architect will own the technical blueprint for how the organization builds, validates, and scales high-quality software where human intellect and autonomous agents seamlessly collaborate. This position requires a combination of extensive engineering judgment, honed over 15 to 20+ years of building massive production systems, and cutting-edge expertise in agentic loops, reinforcement learning edge harnesses, cloud platforms, and advanced AI architectures. The ideal candidate will possess the technical gravity required to shape the engineering culture, tooling, and future of the organization.

Requirements

Typically 15-20+ years of professional software engineering experience building large-scale distributed systems, enterprise architectures, or foundational infrastructure (or 10+ years of hyper-dense experience backed by an advanced research degree).
An M.S. or Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, or a deeply quantitative field is highly preferred, with a strong grasp of both symbolic engineering and probabilistic AI.
Mastery of fundamental computer science, memory management, distributed state, concurrency models, and deep proficiency in languages like Rust, Python, Go, C++, or TypeScript.
A proven track record of architecting mission-critical production systems that operate with high availability, strict security postures, and predictable performance characteristics.
Desire to explore and build new design patterns: Never an incremental thinker, shaping the industry, global economy and positive advancement of new ways humans interact with technology and new patterns that open up all new patterns and products.

Nice To Haves

Production-Grade Agentic Experience: Beyond prompt engineering and casual IDE extensions, you have designed, built, or heavily customized production-grade agentic workflows, multi-agent choreographies, or autonomous code-generation loops.
Cognitive Architecture Fluency: Deep understanding of frontier or open source LLM architectures, context-window dynamics, RAG systems, function-calling mechanics, and fine-tuning paradigms specifically applied to software engineering tasks.
Deterministic Systems for Non-Deterministic Models: Proven ability to build deterministic guardrails around probabilistic models—including complex evaluation harnesses, property-based testing, and automated mutation testing.
Mitigation of Edge-Case Failures: Deep expertise in detecting and defending against advanced agentic failure modes: hallucinated dependencies, subtle architectural regressions, shallow test generation, hidden coupling, and security vulnerabilities.
Tooling Agnosticism: Ability to critically evaluate, bench, and selectively integrate emerging foundation models, AST (Abstract Syntax Tree) parsers, orchestration frameworks, and developer tools with empirical rigor.
Has built or design Agentic Identity, governance and security: Expertise in flow proxy, system design of identity, authorization, compliance and observability systems

Responsibilities

Architect the AI-Native Lifecycle: Define, build, and scale the foundational framework, review standards, and compilation/validation loops for autonomous, agentic software development across the entire enterprise.
Technical Vision & Strategy: Turn highly ambiguous, long-term business goals into concrete, mathematically sound architectural plans, spec-driven development methodologies, and deterministic validation strategies.
Build the Infrastructure for Agents: Design advanced system topologies, multi-agent orchestration frameworks, and context-bounding mechanisms that allow AI agents to safely operate on large, complex codebases. Agentic identity, trust, compliance and governance must be at the forefront of your mind as they are the pivotal decision point for Enterprises.
Establish Rigorous Evals: Lead the creation of next-generation evaluation harnesses, golden test suites, semantic CI/CD gates, and real-time behavioral monitoring to guarantee the safety, security, and deterministic correctness of agentic output.
Pioneer Technical Taste: Act as the ultimate arbiter of code quality, structural integrity, and architectural purity, ensuring that agent-accelerated development reduces technical debt rather than compounding it.
Cross-Functional & Industry Leadership: Partner with Executive Leadership, Product, Security, and Core Infrastructure to align technical roadmaps. Act as a thought leader internally and externally on the future of AI-native engineering.
Mentor and Cultivate Talent: Train and elevate our Principal and Staff engineers, fostering a culture of rigorous engineering judgment in an era of rapid AI automation.
Apply the highest ethics for the use of AI: The goal is to build the standards (or de facto open source code) that leads the industry and other companies build their company upon. You apply the mindset that AI is can benefit humanity and can be used in a creative outlet.