Description
The Experience:
Agents and AI are fast evolving technologies. The Agentic Selling Team within Digital Experience Technology is building production AI agents that revolutionize how Salesforce's global sales organization operates. As Customer Zero for Agentforce, we lead the industry in agent development, pioneering architectural patterns that shape Agentforce products and define the future of enterprise AI agents. We are looking for a Lead Software Engineer who excels in technical leadership, drives architectural decisions, and shapes the technical direction of our agent platform. You will architect sophisticated multi-agent systems using Agentforce, influence product roadmaps, mentor senior engineers, and establish technical standards for agent development at Salesforce.
What You’ll Actually Be Doing
Architect and lead development of sophisticated agent systems using Agentforce, Agent Script, and New Graph Architecture (NGA) serving 15,000+ users with enterprise-grade reliability
Drive technical strategy for the Sales Agent platform including agent memory architecture, RAG patterns, LLM optimization, multi-agent orchestration, and agent-to-agent communication protocols
Lead Customer Zero initiatives working directly with Agentforce platform and product teams to validate new capabilities, provide architectural feedback, and influence product roadmaps
Design and build production AI agents handling complex Seller use cases:
Architect and execute critical platform migrations (Graph to Agent Script, legacy to NGA, Java to Python agents) maintaining zero downtime for production systems
Establish agent observability and quality frameworks including monitoring, analytics, debugging tools, conversation quality metrics, and user satisfaction tracking
Drive innovation in agent memory systems, retrieval augmentation techniques, prompt optimization strategies, and LLM fine-tuning approaches
Lead technical decision-making on system architecture, technology selection, performance optimization, and scalability strategies
Mentor SMTS and MTS engineers through technical guidance, architecture reviews, and career development
Make critical design decisions balancing innovation, reliability, scalability, cost efficiency, and time-to-market
Lead architecture reviews, design sessions, and technical roadmap planning with cross-functional stakeholders
Establish Agentic Engineering best practices, code quality standards, testing frameworks, and deployment strategies for agent development
Build highly scalable, efficient components on microservice multi-tenant SaaS cloud environment with focus on performance, reliability, and operational excellence
Drive end-to-end ownership of major technical initiatives from conception through production delivery and ongoing optimization
Partner with product management, enterprise architects, data science teams, R&D Centers and business leaders to align technical strategy with business objectives
Represent technical team in executive forums, steering committees, and cross-organizational planning sessions
You’re Our Person If…
8+ years of development experience as a software engineer with 5+ years in technical leadership roles
Expert-level experience with backend development in Java, Python, or multiple object-oriented compiled, statically-typed languages (C++, C#)
Deep expertise in AI/ML frameworks with extensive hands-on experience architecting and deploying large language model systems (OpenAI, Anthropic, Claude, Gemini, Llama, etc.)
Proven track record building production agent systems, conversational AI platforms, or multi-agent orchestration frameworks (Agentforce experience highly preferred)
3+ years of hands-on experience with prompt engineering, RAG architectures, agent memory systems, and optimizing LLM performance at scale
Expert knowledge of cloud infrastructure (AWS, GCP, Azure, Heroku) with experience designing and operating large-scale distributed systems
Deep understanding of vector databases, embeddings, semantic search, retrieval optimization, and knowledge graph architectures
Extensive experience with Salesforce platform (Apex, LWC, Data Cloud, Einstein, Platform Events, MuleSoft) or equivalent enterprise platforms
Proven ability to architect RESTful APIs, GraphQL services, event-driven architectures, and microservices at scale
A related technical degree required
Exceptional verbal and written communication skills with proven ability to influence senior leadership and drive technical consensus
Strong experience establishing test-driven development practices, automated testing frameworks, and quality standards for AI/ML systems
Expert-level debugging and problem-solving skills with proven ability to resolve complex production incidents and optimize system performance
Extensive experience with developer tools and platforms: Git, Docker, Kubernetes, Terraform, Spinnaker, CI/CD systems, observability tools (Grafana, Datadog)
Demonstrated success mentoring senior engineers, leading technical teams, and elevating organizational technical capabilities
Track record of delivering large-scale systems used by thousands to millions of users with measurable business impact and high reliability
Even Better If…
Extensive hands-on experience building production agents with Salesforce Agentforce, Agent Builder, or leading agent development platforms
Deep expertise in agentic AI architectures, multi-agent systems, agent-to-agent communication, and orchestration patterns
Advanced knowledge of prompt optimization, LLM fine-tuning, model evaluation, and AI quality assurance techniques
Experience leading Customer Zero programs or early adopter initiatives with direct influence on product strategy
Published research, patents, or recognized contributions to AI/ML or agent development communities
Experience with data engineering at scale including ETL pipelines, real-time processing, and unstructured content ingestion
Proven track record of technical speaking at major conferences or contribution to influential open-source projects
Experience driving technical transformations, platform migrations, or modernization initiatives at enterprise scale
Background in developer platforms, SDKs, or building extensible frameworks used by other engineering teams