Software Engineer - Search & Retrieval

Actively AI is a company focused on building superintelligent machines for Enterprise GTM organizations to enhance productivity. The Senior / Staff Software Engineer - Search & Retrieval will design and scale the systems that power AI agents by developing the search, retrieval, and relevance infrastructure essential for optimal data handling and decision-making.

Responsibilities:

• Build the retrieval layer agents depend on
• Design and scale the search and retrieval infrastructure that feeds Actively's agents, covering indexing, querying, ranking, and filtering across diverse customer data sources
• Turn raw, unstructured data into something retrievable
• Design enrichment and entity extraction systems that pull structure, relationships, and context out of call transcripts, documents, and signals, making them queryable in ways that improve what agents actually see
• Own the Search for Agents Architecture: Define how data gets represented and stored, making deliberate choices about granularity, embedding models, and index configuration for different data types and use cases
• Build and iterate on ranking systems
• Design and deploy reranking layers that maximize relevance for agent queries, and evolve them as data patterns and use cases change
• Develop shared retrieval primitives
• Build the APIs and retrieval interfaces used by the Intelligence, Assistant, and Orchestration teams, balancing flexibility with consistency across consumers
• Own retrieval quality end to end
• Build and maintain evaluation infrastructure using classical IR metrics, task-level success signals, and LLM-based techniques, catching regressions before they affect agent behavior

Requirements:

• 5+ years building and operating retrieval systems in production, across multiple customers, data sources, or domains
• Background in information retrieval or applied ML
• Experience tuning relevance, deploying reranking strategies, and improving result quality in production
• Experience building retrieval pipelines over fast-changing data, including near-real-time indexing, incremental updates, or event-driven ingestion
• Experience with hybrid retrieval approaches that combine semantic search, keyword and lexical matching, and metadata filtering
• Experience designing or evolving retrieval evaluation frameworks using IR metrics, task-level success signals, or automated quality checks
• Understanding of retrieval architecture holistically, including pre-computing versus retrieving at query time, managing index growth, and designing retrieval paths that stay relevant as scale increases
• Prior experience at a search or retrieval-focused company (Elastic, Algolia, Cohere, Pinecone, Weaviate)
• Experience building shared search infrastructure used across multiple teams or products
• Experience with entity resolution, knowledge graph construction, or relationship extraction at scale, particularly over noisy or inconsistently structured source data