Highspot is looking to build the cognitive substrate for intelligent agents that can reason, remember, act, and adapt on behalf of users, directly powering the company's strategic AI roadmap and transforming sales productivity.
Requirements
- Proven track record building distributed systems at scale (Kafka, Kubernetes, AWS, async eventing).
- Strong system design skills across stateless orchestration, caching, multi-tenant scale.
- Experience working with AI agent infrastructure (LangChain, Semantic Kernel, Haystack, etc.).
- Comfort designing tool-use protocols, memory chains, or agent routing logic.
- Experience with agent evaluation frameworks (e.g., LLM-as-a-judge, synthetic evals, golden sets).
- Built multi-agent or recursive reasoning systems.
- Familiarity with observability for LLM behavior: hallucination detection, trace spans, vector drift.
Responsibilities
- Architect AI Agent Infrastructure
- Design agent runtime environments that orchestrate long-running tasks, decisions, and tools.
- Build modular systems for agent memory, contextual state handling, and secure API actions.
- Integrate retrieval-augmented generation (RAG), multi-agent planning, and vector store reasoning.
- Own the backend architecture behind Deal Intelligence pipelines.
- Ensure low-latency data access across MongoDB, PostgreSQL, Kafka, and Solr clusters.
- Define and meet scalability, uptime, observability, and security goals.
Other
- 8+ years experience in backend systems development, including 3+ years in tech lead capacity.
- Excellent communicator and collaborator across product, design, ML, and infrastructure teams.
- Ruby or Typescript proficiency in production environments.
- Past work in sales productivity, CRM, or workflow automation domains.
- Employees are eligible to receive stock options and may also receive other forms of compensation.
