Description

Roles and Responsibilities:

● Core System Development: Design, build, and maintain a high-performance, multithreaded native C++ backend runtime purpose-built for the throughput demands of heavy data workloads.

● Core Library Architecture: Develop and maintain essential internal engine modules, including indexing, networking, handle-based streaming I/O, file storage, and thread/task management.

● Memory & Performance Optimization: Lead memory reduction initiatives to ensure the engine scales efficiently. This includes redesigning internal data structures (such as compressing inverted indexes) to drastically reduce memory footprints and increase data density (documents-per-MB).

● Scale & Reliability Engineering: Profile and debug the runtime in memory-constrained environments (such as Docker containers) to prevent Out-Of-Memory (OOM) failures and ensure stability at scale.

● Cross-Language Integration Support: Ensure the C++ core interfaces seamlessly with high-level programmatic layers and SDKs (like Python and TypeScript). Required (Must-Have) Skills

● Advanced C++ : Deep expertise in high-performance native development, multithreading, memory management, and modern C++ standards.

● Systems Architecture & Build Tools: Experience managing and building complex system libraries utilizing tools like CMake.

● Advanced Data Structures: Strong background in optimizing standard data structures (e.g., migrating from standard vectors to highly compressed, performance-oriented formats).

● Low-Level Hardware Optimization: Experience with SIMD bit-packing (AVX2/NEON) and fast decoding algorithms for performance-critical execution paths.

● Docker & System Profiling: Proficiency in benchmarking, profiling, and optimizing systems within containerized environments under strict memory constraints. Good-to-Have Skills

● Advanced Compression Techniques: Familiarity with advanced data encoding methods such as delta encoding, Elias-Fano encoding, TurboPFor, and Roaring Bitmaps for handling both sparse and dense datasets efficiently.

● Cross-Language Interoperability: Experience building or maintaining systems that require seamless interoperability with Python, JavaScript, or TypeScript SDKs.

● Systems Debugging (Java/C): Working knowledge of Java or C to assist in debugging minor legacy integrations or external document parsers when necessary.

● LLM & Vector DB Integrations: Hands-on experience interacting with diverse Large Language Model (LLM) APIs

● Multi-Agent Orchestration: Practical experience implementing or integrating agentic reasoning frameworks, specifically CrewAI and LangChain, to chain agents and share memory across multi-step execution runs.

● RAG & Multimodal Workflows: Deep understanding of applied ML concepts including embedding models, chunking strategies, Optical Character Recognition (OCR), Named Entity Recognition (NER), and PII anonymization pipelines

● AI Protocols & Tooling: Experience working with the Model Context Protocol (MCP) to expose pipelines and native C++ functionalities as callable tools for AI assistants. Understanding of how modern automated coding agents (like Claude and Cursor) interact with codebases Related Domain Knowledge

● Search Engineering: Deep understanding of search index architectures (like inverted indexes), optimal posting list compression, and high-speed data retrieval capable of microsecond intersection speeds.

● Data Pipelines & Streaming I/O: Knowledge of real-time data processing, stream management, and engineering production-scale systems without bottlenecks.

● Telemetry & Observability: Understanding of building engine-level hooks to track execution latency, memory consumption, and call trees in real time

Key Skills

Education

Any Gradute