Responsibilities:
Design and build scalable platform components leveraging advanced retrieval via query planning, semantic and hybrid search, metadata-aware search, and LLM generation
Design and build optimized indexing pipelines for structured and unstructured data
Build backend services for semantic and hybrid retrieval, knowledge graph construction, and retrieval orchestration
Improve retrieval quality through evaluation and observability frameworks
Design APIs for internal and external user and agentic consumers
Optimize latency, throughput and cost across large-scale inference and retrieval workloads
Drive technical direction for reliability and security
What Youll Bring to the Table:
To thrive in this role, you don't need to check every single box, but you should be deeply passionate about how to turn data into knowledge.
Systems Expertise
Architectural Depth: You have a proven track record (typically 6+ years) of shipping production-grade backends for large-scale systems. You dont just write code; you design for high throughput, low latency, and long-term maintainability.
Data Engineering Savvy: Youre comfortable building high-throughput indexing pipelines that handle both the messy world of unstructured data and the rigid world of structured schemas.
AI & Retrieval
Retrieval Intuition: You understand that "search" is more than just a keyword match. You have direct experience (or deep theoretical knowledge) in semantic search, vector databases, hybrid retrieval strategies, or with traditional search engines like Elastic or OpenSearch.
RAG & Orchestration: You understand the nuances of Retrieval-Augmented Generation (RAG) patterns, from embedding pipelines and hybrid search techniques to how query planning and metadata filtering can make or break an LLM's performance.
Technical
Language Fluency: You are an expert in at least one major language like Go, Rust, C++, Java, or Python.
Infrastructure: Familiarity and experience with modern infrastructure tools, such as Kubernetes, cloud-native architectures, and observability frameworks, as well as infrastructure-as-code tools like Terraform or Pulumi.
Ownership & Impact
Product Thinking: You don't just build to spec; you build for the user. You can design clean, intuitive APIs that both human developers and autonomous agents will love.
Ambiguity Navigator: Youre comfortable in a high-growth environment. You prefer "owning a problem" over "executing a ticket."
Bonus Points
Experience building multi-tenant SaaS platforms.
Experience with retrieval evaluation frameworks-knowing how to actually measure "good" search results.
Experience with query planning or agentic reasoning loops (e.g., teaching a system how to break down a complex prompt into multiple specific steps).
