Job VC

Requirements:
Strong backend development experience with
C++
(the bulk of the backend is built on a custom in-house framework)
Hands-on experience with
AWS
, particularly
S3
Proficiency with
Protobuf
Experience deploying and operating services on
Kubernetes
, including performance-driven traffic routing to pods
Performance engineering
skills — hash-based routing, SSD-based caching, and memory-mapped files
Solid systems / low-level fundamentals (there is no off-the-shelf framework to rely on — much of the stack is custom)
Ability to work highly autonomously and drive work forward with minimal supervision
Strong communication skills and experience working in distributed teams (Europe/Ukraine time zone; ~1–2 hours of daily overlap with a US-based team)
Hands-on experience with AI-assisted development tools — e.g.
Claude Code
and
Codex
— including AI skills, plugins, and
MCP
(Model Context Protocol), with a clear understanding of how to boost personal productivity and code quality using AI tooling
Nice-to-Have:
Familiarity with
OpenTelemetry
/ observability tooling
Understanding of
LevelDB SSTable
concepts and sorted, time-keyed data structures
Familiarity with
Python
(used only for a small metadata/auth service)
Basic
DevOps
skills
Key Responsibilities:
Optimize the performance of the
C++ data-streaming backend
— efficient delivery of large recorded datasets to the browser
Work on
infrastructure-level optimizations
: traffic routing to Kubernetes pods, hash-based routing, SSD-based caching, and memory-mapped files
Operate within a
custom data-handling stack
— a C++ framework, a custom HTTP server, and a proprietary data format built on top of LevelDB SSTables and Protobuf
Take ownership of performance work end-to-end, proactively identifying bottlenecks and driving solutions independently
Collaborate with a primarily US-based team with ~1–2 hours of daily overlap, while working largely independently
Participate in code reviews and design discussions
About the Project:
You'll join the engineering team of a leading technology company building
autonomous mobility and robotics systems
. The team develops an internal
data visualization platform
— a "video and data player" that renders 3D scenes, lidar, and audio recorded by autonomous vehicles. This role sits on the
performance work stream
: the backend reads on-vehicle data stored in
S3
, deserializes it from a custom, time-keyed format, and streams it to the browser. The data-transfer service is implemented in
C++
, and most of the platform's performance gains are expected to come from the backend.
This is a long-term engagement for a strong systems engineer who enjoys low-level performance work and is comfortable ramping on a heavily custom stack with high ownership and minimal supervision.