Senior, Member of Technical Staff

Salesforce•Indianapolis, IN

About The Position

Salesforce is the #1 AI CRM, where humans with agents drive customer success together. Here, ambition meets action. Tech meets trust. And innovation isn’t a buzzword — it’s a way of life. The world of work as we know it is changing and we're looking for Trailblazers who are passionate about bettering business and the world through AI, driving innovation, and keeping Salesforce's core values at the heart of it all. Ready to level-up your career at the company leading workforce transformation in the agentic era? You’re in the right place! Agentforce is the future of AI, and you are the future of Salesforce. Agents and AI are fast evolving technologies. The Agentic Selling Team within Digital Experience Technology is building production AI agents that transform how Salesforce's global sales organization operates. As Customer Zero for Agentforce, we pioneer agent development patterns that influence product strategy and define enterprise AI standards. We are looking for a Senior Software Engineer who thrives in a fast-paced environment, delivers high-quality solutions independently, and drives technical excellence. You will architect and build sophisticated agent systems using Agentforce, Agent Script, and New Graph Architecture while integrating with Salesforce CRM, Data Cloud, and external platforms.

Requirements

6+ years of development experience as a software engineer with demonstrated growth in technical complexity and scope
Strong experience with backend development in Java, Python, or at least one object-oriented compiled, statically-typed language (C++, C#)
Deep knowledge of AI/ML frameworks and hands-on experience working with large language models (e.g., OpenAI, Anthropic, Claude, Gemini, Llama)
Proven experience with prompt engineering, RAG architectures, and building production LLM-based applications or agents
Experience with conversational AI, chatbots, or agent development platforms (Agentforce experience strongly preferred)
Experience with cloud infrastructure (e.g., AWS, GCP, Heroku) and designing scalable, distributed system architectures
Proficiency in data processing, vector databases, embeddings, semantic search, and retrieval optimization
Strong understanding of Salesforce platform (Apex, LWC, Data Cloud, Platform Events) or equivalent enterprise platform experience
Experience with RESTful APIs, GraphQL, event-driven architectures, and microservices patterns
A related technical degree required
Excellent verbal and written communication skills with ability to influence technical decisions and collaborate across organizations
Strong experience in test-driven development including unit testing, integration testing, and end-to-end automation for AI systems
Proven ability to debug complex production issues, optimize system performance, and resolve customer-impacting problems
Experience with developer tools such as Git, Docker, Kubernetes, Terraform, CI/CD pipelines (Jenkins, GitHub Actions, Spinnaker)
Track record of mentoring engineers and elevating team technical capabilities
Experience delivering large-scale features used by thousands of users with measurable business impact

Nice To Haves

Hands-on experience building agents with Salesforce Agentforce or Agent Builder
Experience with agent orchestration frameworks, multi-agent systems, and agentic AI architectures
Deep expertise in prompt optimization, fine-tuning LLMs, and model evaluation techniques
Experience with Customer Zero or early adopter programs influencing product development
Knowledge of data engineering, ETL pipelines, and content processing at scale
Experience with observability tools (Grafana, Datadog) and monitoring agent systems in production
Contributions to technical communities, open-source projects, or conference speaking

Responsibilities

Design and build sophisticated agent architectures using Agentforce Builder, Agent Script, and NGA for production systems serving 15,000+ users
Architect multi-node agent orchestration, sub-agent patterns, and agentic workflows for complex sales use cases.
Lead implementation of agent memory systems, context management, and conversation state handling for personalized experiences
Develop and optimize RAG patterns, retrieval strategies, and prompt engineering techniques to improve agent quality and accuracy
Build scalable integrations connecting agents to Salesforce Data Cloud, Einstein, MuleSoft, and external APIs and MCP.
Design and implement content ingestion pipelines processing structured and unstructured data (PDFs, web content, documents) for agent knowledge bases
Drive platform migrations (e.g., Graph to Agent Script, legacy to NGA) while maintaining zero downtime for production systems
Implement agent observability, monitoring, and debugging capabilities to track conversation quality and user satisfaction
Mentor junior engineers through code reviews, technical guidance, and knowledge sharing
Make critical technical decisions on agent design patterns, performance optimization, and scalability
Work in an Agentic Agile engineering model leading design discussions, implementation, and delivery of major features
Participate in architecture reviews and contribute to technical roadmap planning
Lead UAT efforts, production deployments, and maintain high availability standards through bi-weekly release cycles
Design and build smart agent systems that help over 15,000 users do their jobs better.
Create systems that help agents "remember" conversations and manage data so they can provide personal experiences.
Build connections between agents and tools like Salesforce Data Cloud and other apps to make sure everything works together smoothly.
Mentor junior team members by reviewing their code and sharing your technical knowledge.
Lead design discussions and make big decisions about how we build features that scale.
Test and improve our systems to make sure they run perfectly and stay reliable for all our users.