Lead Member of Technical Staff

Responsibilities

• 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

• 8+ years of development experience as a software engineer
• 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, Mule Soft) 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