Lead Software Engineer (C++)

Lead Engineer C++

Let’s be unstoppable together!

Circana is a leading provider of technology, AI, and data solutions for consumer packaged goods companies, manufacturers, and retailers. Our predictive analytics and Liquid Data® platform help clients measure market share, uncover consumer behavior, and drive growth—powered by six decades of expertise and an expansive, high-quality data set.

At Circana, we are fueled by our passion for continuous learning and growth, we seek and share feedback freely, and we celebrate victories both big and small in an environment that is flexible and accommodating to our work and personal lives. We’re a global company dedicated to fostering inclusivity and belonging. We value and celebrate the unique experiences, cultures, and viewpoints that each individual brings. By embracing a wide range of backgrounds, skills, expertise, and beyond, we create a stronger, more innovative environment for our employees, clients, and communities. With us, you can always bring your full self to work. Join our inclusive, committed team to be a challenger, own outcomes, and stay curious together. Circana is proud to be Certified™ by Great Place To Work®. This prestigious award is based entirely on what current employees say about their experience working at Circana. Learn more at www.circana.com.

Role Overview

We are seeking Senior Staff Engineer to drive design, evolution, and execution of our next-generation, massively parallel processing (MPP) clustered database engine (Whitebox) that currently powers large-scale retail and consumer analytics solutions across Circana clients in 22+ countries and serving millions of queries every day in real-time against massive data sets . This is a highly technical role for an expert who bridges the gap between High-Performance Computing (HPC) and Big Data systems engineering and low-latency machine learning infrastructure and involves database internals, distributed systems, performance engineering, data processing at scale.

In this role, you will be one of the primary designers and developer responsible for building low-latency, high-throughput distributed database kernels. You will design bare-metal optimized software layers, ensuring our database product fully exploits modern multi-core, vectorized hardware and distributed network fabrics to process terabyte/petabyte-scale datasets and where appropriate, seamlessly executes highly performant analytics and in-database ML inference directly on relational and the occasional vector datasets.

Job Responsibilities

• Architecture & Design: Play a key role in core architectural choices and roadmap for our distributed database kernel, including query execution engines, custom/hybrid columnar storage layers, distributed transaction managers, and cluster coordination protocols.
• Low-Level Development: Write, optimize, and maintain highly performant, production-ready backend code utilizing modern C++ (C++20/23).
• Parallel Execution Planning: Architect MPP execution engines that distribute, schedule, and execute queries across several dozens to hundreds of nodes using MPI and hybrid OpenMP models.
• Hardware Optimization: Profile and eliminate execution bottlenecks by implementing explicit SIMD vectorization (AVX-512, ARM Neon, SVE) and ensuring absolute cache locality (L1/L2/L3).
• Distributed Memory & Networks: Design ultra-low latency cluster communication subsystems utilizing RDMA, RoCE, or kernel-bypass tech (DPDK).
• In-Database ML Framework Design: Architect and implement a native, highly performant, zero-copy ML execution framework directly inside the MPP engine to eliminate data serialization and transport bottlenecks between the database and external AI pipelines.
• Functional & High-Performance Algorithms: Develop mathematically rigorous, cache-oblivious, and highly vectorized algorithms for real-time statistical computations, matrix operations/manipulations on clustered data
• Vector & Embedding Infrastructure: Design and optimize or embed/reference distributed high-dimensional vector storage subsystems, custom SIMD-accelerated indexing structures (e.g., HNSW, IVF-PQ), and parallelized approximate nearest neighbor (ANN) search algorithms.
• Be comfortable working in a cross country/multi time zone team of elite systems engineers, implementing as well as conducting rigorous peer design and development reviews
• Collaborate with cross-func…