Staff Software Engineer

The Discovery team sits at the core of Harmonic’s product and data engine. We make it possible to search, research, analyze, compare, and evaluate across the entire universe of startups (we track tens of millions of companies, hundreds of millions of operators and, tens of thousands of investors along with their deal activity, and counting). We source and ingest data from first-, second- and third-party sources, including hundreds of fragmented and unstructured sources, and turn them into structured insights and searchable indices. Recently, we built the industry leading agentic layer for startup search and research, that’s unlocking new paradigms for VCs to make sense of this vast amount of data on startups and automate critical tasks in their sourcing and diligence workflows.

We’re in the middle of a massive platform shift where AI and LLMs are transforming what "software" is. Agentic product- and user-experience patterns will be spelled out in playbooks before long – and we’re building those playbooks, not waiting for them. This includes conversational interfaces, deep research, dynamic agentic frameworks purpose built for venture, and AI-first product workflows. We’re looking for folks that want to help redefine software and push on this frontier with deep curiosity, an insatiable growth mindset, and high agency.

To learn more about the team:

• Explore Working with Sang
• Check out your Scout focused teammates Austin, Yesh, and Kelvin
• Explore the Team Page. We’re a mix of ex-founders and seasoned engineers from top engineering institutions like Google, LinkedIn, Microsoft and Meta.

Scope of the role:

• Architect the core intelligence behind Scout
  • Own the end to end architecture of our sourcing engine from data ingestion, ranking, personalization, and model orchestration. 
  • Define scalable frameworks for retrieval, reranking, and LLM driven evaluation to ensure we deliver highly personalized and high quality results.
  • Create architectural patterns that integrate Scout seamlessly with our existing products to power repeatable sourcing workflows.
• Lead agentic experimentation and evaluation
  • Drive technical discovery for emerging technologies (e.g. memory systems, schema, prompt libraries, embedding models, and agentic frameworks).
  • Improve and extend our evaluation pipelines to test new models and determine lifts in specific parts of our product.
  • Build systems that allow fast iteration without compromising quality or reliability. Our priorities are reliability, performance, cost, and then developer productivity.
• Shape AI native product experiences
  • Partner with product and design to define patterns that make LLM powered sourcing intuitive and fast.
  • Translate ambiguous product goals into scalable technical designs that unblock new workflows for our users.
  • Establish best practices for building AI-first UX patterns (agentic flows, async interactions, structured outputs).
• Provide architectural leadership across engineering
  • Mentor and guide engineers on the team raising the bar for system design, documentation, and technical decision making. 
  • Drive clarity in cross team architecture with Flow, Data, and Infra ensuring Sourcing evolves as a cohesive, maintainable system.
  • Set long term technical direction for how we build AI powered sourcing systems.

Background we’re looking for:

• 7-8+ YoE building distributed systems or large scale backend architecture.
• Designed and scaled search, recommendation, or ranking systems that balance precision, recall, and performance.
• Led or heavily contributed to ML or LLM integrations in production.
• A track record of technical leadership mentoring others, introducing frameworks, and influencing technical direction.
• Strong experience with data-intensive systems, asynchronous processing, or event-driven architectures.

Pay

$210-280k Salary + Equity depending on the level

Here’s our interview process:

1. Recruiter Screening: 20 mins
2. Technical Screening (Debugging): 45 mins
3. Technical Screening (System Design): 45 mins
4. Jam Session: 2 hours 
5. Behavioral interviews with our Head of Engineering and CEO: 30 mins each
6. References