Software Engineering SMTS

Salesforce•San Francisco, CA

2d•$178,900 - $246,000

About The Position

Salesforce is looking for a Senior Member of Technical Staff (SMTS) - AI Software Engineer to join the team driving the development and delivery of Agentforce. This role requires a strong backend developer who will play a pivotal role in maintaining our core execution engines, handling complex orchestration, and ultimately building the next generation of intelligent agents. You will work on impactful generative AI platforms, applications, and products used by millions of people every day, ensuring their stability, security, and future evolution. The Team We are a group of Generative AI Application Engineers who are passionate about designing products and building intelligent agents that work alongside humans to drive customer success 24/7. We love to learn, teach, and help each other, and we seek core product developers with a collaborative attitude, strong problem-solving skills, and openness to others’ ideas. The Role As an SMTS, your journey will bridge the optimization of our current core systems with the creation of next-generation AI reasoning. Phase 1 (Legacy Optimization): You will start by taking ownership of our legacy React Planner. This is a tricky, business-critical system that requires a developer who loves deep-dive problem-solving. Your initial focus will be on driving stability, resolving complex bugs, addressing customer escalations, and implementing critical security fixes. While new feature development will be lighter in this phase, your work will be vital to keeping the platform robust. Phase 2 (Next-Gen Evolution): As you master the architecture, you will transition to working on our new reasoner. Here, you will actively build out new reasoning features, integrate generative AI services, design pipelines, and implement citations/guardrails for LLMs. You will participate in the end-to-end AI product development lifecycle, collaborating with AI Platform Engineers and Software Engineers to develop scalable, reusable workflows.

Requirements

5+ years of industry experience In software engineering, with a proven track record as a core backend product developer (This is a core R&D developer role, not a CCE or FDE position).
Strong programming skills in Java (the role starts heavily in Java) with a solid understanding of object-oriented design.
Strong programming skills in Python, with experience or a strong interest in building ML pipelines.
Bachelors (or) Masters degree in Computer Science, Software Engineering, or related STEM field with strong competencies in algorithms, data structures, and software design.
Excellent debugging and triage skills; a passion for digging into legacy codebases to solve complex bugs and security vulnerabilities.
Experience with distributed, scalable systems and modern data storage, messaging, and processing frameworks (e.g., Kafka, Docker, Spark).
Basic understanding of deep learning, machine learning algorithms, LLMs, and prompt engineering.
Excellent problem-solving skills; the ability to tackle problems the world has yet to solve.

Nice To Haves

Experience developing applications/services for complex business use cases and large amounts of unstructured data.
Experience with conversational AI and fine-tuning methods for LLMs.
Strong written and verbal communication skills with a track record of driving collaboration across multiple technical teams.

Responsibilities

Maintain, debug, and optimize the legacy React Planner engine, ensuring high availability, security, and rapid resolution of customer issues.
Transition into designing and building new reasoning features and capabilities for the next-generation Agentforce reasoner.
Build and own end-to-end scalable services that can be integrated with numerous applications, support thousands of tenants, and operate at scale in production.
Drive system efficiencies through automation, including capacity planning, configuration management, performance tuning, monitoring, and root cause analysis.
Participate in periodic on-call rotations and be available to resolve critical production issues.
Collaborate with Product Managers, Application Architects, Data Scientists, and Deep Learning Researchers to bring innovative technologies to production.