Distributed Systems Engineer – Vector Database

3 weeks ago

Pune, Maharashtra, India HI Technology & Innovation Full time

About the Role

HI Technology & Innovation is collaborating with a pioneering database company to evolve a single-threaded, command-line vector database proof-of-concept, originally written in C#, into a demonstrable, parallelized prototype. We're looking for an experienced Distributed or Parallel Processing Engineer to lead the development of a lightweight "controller + wrapper" layer that adds multi-instance orchestration, parallelism, and query merging capabilities to the current system.

This is a high-impact, fast-paced role ideal for someone with strong distributed systems thinking and a pragmatic, get-it-done engineering mindset.

What You'll Tackle

  • Design and implement a wrapper/controller layer around the existing single-threaded vector DB POC.
  • Enable sharding and parallel loading of large vector datasets across multiple instances.
  • Implement logic to dispatch and coordinate parallel queries, aggregate candidate vectors, apply a pluggable distance metric (e.g., Euclidean, cosine similarity, SAD/Manhattan), and merge and sort results before returning to the caller. 
  • Expose bothcommand-line and REST interfaces to interact with the system.
  • Output clear timing metrics to demonstrate speed-ups from parallel execution.
  • Deliver a working, testable prototype—production-ready polish is not required.

What We're Looking For

  • Deep expertise in distributed computing and parallel processing, including MapReduce-style design patterns, data sharding, and inter-process communication (IPC).
  • Proven track record as a senior engineer who can work independently, move quickly, and deliver results with minimal oversight.
  • Strong problem-solving skills and practical experience building distributed systems and prototypes.
  • Comfort working across multiple languages and runtimes. Choose whatever tech stack gets the job done fastest (Python, C#, C, etc.).
  • Ability to clearly demonstrate and benchmark performance improvements.

Engagement Snapshot

  • Timeline: Short-term, estimated 5–10 days of focused work.
  • Start Date: ASAP
  • Location: Remote
  • Deliverables: Fully functional parallel prototype with CLI + REST interfaces, benchmark metrics, and sharded query support.

Ready to build something fast and clever? Apply now and help bring this proof-of-concept to life.

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