Lead Software Engineer

Salesforce Salesforce · Enterprise · Austria · Remote

Lead Software Engineer on the Agentic Data team, responsible for building the foundational layer for intelligent agents at Salesforce scale. This involves architecting and implementing high-scale systems for agent data access, governance, and reasoning, with a focus on distributed systems, AI infrastructure, and enterprise trust. The role requires a deep understanding of the LLM lifecycle, agentic frameworks, and various data systems.

What you'd actually do

  1. Architect and implement high-scale systems that manage agent data access patterns, including guardrails, traceability, telemetry, and auditability
  2. Contribute to the design of the technical infrastructure required for the future of agents and be deeply involved in code production, code reviews, and design decisions
  3. Partner with Product, Security, and Business Units to ensure agents operate with the correct data access permissions and governance controls
  4. Lead technical direction for the team — set standards, mentor engineers, and drive alignment across a cross-functional group of stakeholders
  5. Adopt and advocate for AI-first development patterns across the engineering organisation

Skills

Required

  • Java
  • Python
  • Kotlin
  • Scala
  • Rust
  • Go
  • LangChain
  • PydanticAI
  • LLM lifecycle
  • prompt engineering
  • RAG
  • agentic reasoning patterns
  • distributed systems
  • platform engineering
  • vector databases
  • relational databases
  • graph databases
  • event-driven architecture
  • Kafka
  • large-scale data processing

Nice to have

  • Claude Code
  • Cursor
  • GitHub Copilot
  • guardrails for autonomous systems
  • permissions
  • data masking
  • FedRAMP
  • HIPAA

What the JD emphasized

  • 8+ years of industry experience with a proven track record of leading large-scale distributed systems or platform engineering
  • Deep understanding of the LLM lifecycle, including prompt engineering, RAG (Retrieval-Augmented Generation), agentic reasoning patterns (such as ReAct and Chain-of-Thought), and building MCP servers
  • Hands-on experience with agentic frameworks such as LangChain or PydanticAI
  • Familiarity with a wide variety of data systems: vector, relational, and graph databases, event-driven architecture (Kafka), and large-scale data processing

Other signals

  • building foundational layer for intelligent agents
  • architecting and implementing high-scale systems for agent data access
  • deep understanding of LLM lifecycle and agentic reasoning patterns