The Agentforce Engines & Experiences team is at the heart of Salesforce's AI-native future. We build the core backend infrastructure and platform capabilities that power Agentforce — enabling intelligent, autonomous agents to reason, act, and deliver outcomes for customers at scale. Our systems are built on Java and Python, deployed on cloud infrastructure, and designed for high availability, low latency, and massive scale.

We're looking for a hands-on technical leader who thrives in a fast-moving AI environment, is excited about building foundational infrastructure, and wants to shape how enterprise AI agents are built and run. As a Senior Member of Technical Staff, you will drive architecture, set engineering standards, and work closely with Product Management, Research, and Platform teams to push the boundaries of what AI can do for our customers.

Key Responsibilities

* Technical & Engineering Leadership: Champion and enforce best-in-class engineering practices across architecture reviews, code quality, scalability design, and security standards for AI platform services.
* AI Infrastructure: Design, build, and operate high-performance backend systems that serve as the execution layer for Agentforce — including agent orchestration, reasoning pipelines, tool invocation, and memory services.
* Architecture & Strategy: Collaborate with engineering leadership and architects to define and evolve the long-term technical roadmap for Agentforce engines and experiences.
* Emerging AI Technology: Spearhead research, prototyping, and integration of AI/ML technologies and agentic frameworks to enhance product capabilities, performance, and developer experience.
* Cross-Functional Collaboration: Partner closely with Product Management, Applied AI Research, and Platform teams to translate business requirements into scalable, production-grade systems.
* Mentorship: Elevate engineering talent across the team through hands-on code reviews, architecture guidance, and a culture of continuous learning.

Must Haves

* BS or higher in Computer Science or a related technical field.
* 5+ years of professional software engineering experience, with a demonstrable focus on large-scale, distributed, or AI/ML-intensive backend systems.
* Deep proficiency in Java and/or Python, with production experience building and operating high-throughput services at scale.
* Proven experience designing, building, and maintaining production services on AWS or equivalent cloud platforms (GCP, Azure).
* Strong knowledge of distributed systems concepts: consistency, fault tolerance, service mesh, observability, and performance tuning.
* Experience designing and maintaining RESTful and/or gRPC APIs for mission-critical, latency-sensitive workflows.
* Excellent written and verbal communication skills, with the ability to drive alignment across engineering, product, and research stakeholders.
* A passion for teaching, mentoring, and building high-performing engineering teams.

Nice to Haves

* Hands-on experience building or integrating LLM-based systems, agentic frameworks, or AI orchestration pipelines in production environments.
* Familiarity with AI/ML model serving infrastructure, vector stores, embeddings, or retrieval-augmented generation (RAG) patterns.
* Experience with Kubernetes, container orchestration, and cloud-native infrastructure (AWS EKS, Lambda, SQS, S3, etc.).
* Strong background in observability — distributed tracing, metrics, alerting, and on-call best practices in high-traffic production environments.
* Experience with multi-tenant SaaS platforms and enforcing security, compliance, and data isolation at scale.
* Prior work on developer-facing platforms or internal APIs used by other engineering teams.