Lead Member of Technical Staff

Salesforce Salesforce · Enterprise · Indianapolis, Texas - Dallas, IN

Salesforce is seeking a Lead Software Engineer to architect and lead the development of production AI agents and multi-agent systems using their Agentforce platform. The role involves driving technical strategy for the Sales Agent platform, including memory architecture, RAG, LLM optimization, and agent orchestration, while also establishing observability and quality frameworks. The engineer will mentor other engineers and make critical design decisions for scalability and reliability in a SaaS cloud environment.

What you'd actually do

  1. 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
  2. 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
  3. Lead Customer Zero initiatives working directly with Agentforce platform and product teams to validate new capabilities, provide architectural feedback, and influence product roadmaps
  4. Design and build production AI agents handling complex Seller use cases:
  5. Architect and execute critical platform migrations (Graph to Agent Script, legacy to NGA, Java to Python agents) maintaining zero downtime for production systems

Skills

Required

  • 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

Nice to have

  • Agentforce experience highly preferred

What the JD emphasized

  • production AI agents
  • multi-agent orchestration
  • Agentforce experience highly preferred
  • 3+ years of hands-on experience with prompt engineering, RAG architectures, agent memory systems, and optimizing LLM performance at scale
  • Deep expertise in AI/ML frameworks with extensive hands-on experience architecting and deploying large language model systems

Other signals

  • production AI agents
  • multi-agent orchestration
  • Agentforce platform