Software Engineer, Data Acquisition

As a Software Engineer in Data Acquisition at Nascent, you own the systems that feed the trading and research operations with the data they need to compete. You build and operate the web scraping and data acquisition infrastructure that runs 24/7 across a heterogeneous fleet of machines, providers, and operating systems. This is a roughly 50/50 split between software engineering and operations: half your time you're writing production code in Rust to build new scrapers, defeat anti-bot countermeasures, and architect resilient pipelines; the other half you're deep in logs, monitoring dashboards, and fleet health, diagnosing failures, tuning proxies, and keeping a distributed system humming across mixed infrastructure.

What you'll do

• Build and maintain production-grade web scraping systems in Rust, designing scrapers that are resilient to site changes, rate limiting, CAPTCHAs, and evolving anti-bot countermeasures.
• Operate and monitor heterogeneous distributed infrastructure spanning multiple cloud providers, bare metal, and mixed operating systems, owning uptime and not just deployments.
• Diagnose production issues from raw logs and telemetry, building observability into every system you ship so problems surface before they cascade.
• Design and implement proxy management, rotation strategies, and network-layer evasion techniques to maintain reliable data acquisition at scale.
• Develop tooling for fleet health monitoring, automated alerting, and self-healing infrastructure across diverse machines and hosting environments.
• Collaborate with analysts and researchers to understand data requirements, prioritize new source integrations, and ensure data quality and freshness meet trading-grade standards.
• Reverse-engineer web applications and APIs by inspecting network traffic, deobfuscating JavaScript, and adapting to adversarial changes in target sites.
• Continuously improve system reliability, throughput, and maintainability through refactoring scraping pipelines, optimizing connection handling, and reducing operational toil via automation.
• Deploy and maintain agentic workflows for data source discovery, onboarding, and troubleshooting, using LLM-based agents to automate the identification of new sources, accelerate integration, and surface and resolve failures in existing pipelines.

What you bring

• 2 to 5 years of professional software engineering experience with strong systems or backend fundamentals, shipping production-grade code that runs in anger.
• Proficiency in at least one major programming language such as Go, Python, C++, or Java.
• Deep understanding of networking fundamentals: TCP/IP, DNS, HTTP internals, CDNs, proxies, load balancing, and queue handling.
• Hands-on experience with web scraping or data acquisition at scale, including familiarity with anti-bot and anti-automation countermeasures and evasion techniques.
• Demonstrated experience operating heterogeneous distributed infrastructure across mixed OS, hardware, and hosting providers, not just deploying to a single cloud provider.
• Strong log analysis and monitoring skills; you can diagnose issues from raw logs and build observability into systems you own.
• Hands-on experience building or operating agentic workflows using LLM-based agents and tool-use pipelines for automation, data extraction, or system orchestration.
• A builder mindset that extends beyond code: you don't consider a project done when the PR merges, but when it is stable in production for weeks.
• Genuine interest in the cat-and-mouse game of web scraping at scale: anti-bot systems, browser fingerprinting, proxy rotation, and the constant adaptation it requires.
• Comfort navigating messy, heterogeneous infrastructure and making it better over time.
• Energy for operational puzzles: tracing failures across distributed logs, identifying subtle network degradation, or figuring out why a scraper that worked yesterday is now blocked.
• Fluency with agentic workflows and LLM-based tooling; you know how to design and operate AI agents and reach for them when they are the right tool.
• Strong networking intuition; you think in terms of TCP connections, DNS resolution, HTTP headers, and proxy chains, not just API calls.
• Comfort in less-structured environments where you prioritize your own work and take ownership of outcomes.

Nice to have

• Production experience with Rust, the primary language of the stack.
• Proficiency in Python for scripting, prototyping, and analyst-facing tooling.
• Experience with cloud providers such as AWS, GCP, or DigitalOcean and managing infrastructure across multiple providers simultaneously.
• Background in high-throughput HTTP at scale, including proxy management, VPN and routing optimization, and connection pooling.
• Exposure to real-time or latency-sensitive systems; HFT-adjacent experience is a plus.

What we offer

• Remote-first, distributed team with frequent in-person sprints and retreats. Montreal proximity is preferred for in-person collaboration, but not a hard requirement. North American or European time zones work best for team overlap.
• Competitive total compensation with strong bonus upside tied to performance.
• Hardware and home-office stipend, conference and learning budgets.
• Comprehensive health benefits including medical, dental, and vision coverage, plus life insurance.
• Open vacation policy with flexible work hours and location.
• 16 weeks fully-paid parental leave with supported return to work.
• Retirement matching.

About Nascent

Founded in 2020, Nascent combines venture and market pedigree with product-grade engineering to turn research into revenue. The team operates from a base of permanent capital, deploys assets across liquid and long-term strategies, and has backed 100+ early-stage teams. Nascent focuses on models, low-latency infrastructure, and resilient systems that compound performance over time in open financial markets.