The Software Engineering PMTS - Search & Personalization joins the AgentExchange team to lead the engineering vision for the AI-powered discovery layer. This role involves designing and delivering next-generation agentic search, including multi-turn conversational discovery, AI-generated summaries, and personalized recommendations. You will build scalable indexing pipelines for new asset types, manage search infrastructure, and drive platform modernization from Heroku to Falcon. Key responsibilities include owning technical vision for discovery at scale, ensuring 99.95% availability, and mentoring engineers. Required expertise includes enterprise-scale search engines like Elasticsearch, OpenSearch, or Solr, and backend languages such as Node.js or Java. You will solve the complex problem of transforming keyword matching into a context-aware, multi-turn agentic discovery experience powered by GenAI, personalization signals, and real-time behavioral data.
Lead the architectural design and delivery of GenAI search, multi-turn agentic discovery, and personalization services.
Define the Northstar architecture for the Search & Personalization domain to align with the AgentExchange marketplace strategy.
Develop scalable, low-latency indexing pipelines for new asset types including agents, tools, and skills.
Drive platform modernization by migrating search services infrastructure from Heroku to Falcon.
Own engineering excellence by managing observability, latency budgets, 99.95% availability targets, and security risk governance.
Act as the technical authority by providing guidance, mentorship, and sponsorship to senior and junior engineers.
Collaborate cross-functionally with Product and Platform teams to deliver unified catalog indexing and contextual search surfaces.
What we're looking for
10+ years of experience in software engineering with a track record of technical leadership on enterprise-scale search, recommendation, or personalization systems.
Proven ability to define and drive long-term technical vision and architectural roadmaps for large, complex search or ML-infused platform domains.
Deep expertise in search engine internals including indexing pipelines, ranking, query understanding, and relevance tuning.
Experience with search infrastructure such as Elasticsearch, OpenSearch, Solr, or equivalent.
Proficiency in Node.js, Java, or equivalent for high-throughput search services.
Experience designing and delivering recommendation or personalization systems using collaborative filtering, content-based ranking, or behavioral signal processing.
Hands-on experience integrating LLMs or GenAI into search products for summaries, query expansion, semantic search, or conversational retrieval.
Experience with real-time and near-real-time data pipelines for indexing and signal ingestion.
Java
SQL
PL-SQL
Node.js
Express
Hapi
RDBMS
NoSQL
GenAI
LLM
RAG
Vector Search
Data Pipelines
Distributed Data Processing
Data Lake
Lakehouse
API Development
CI/CD
Agile
Streaming
Event-driven Architecture
Data Governance
Metadata Management