Lead Software Engineer

Location:

Atlanta, GA - Hybrid 3X a week onsite The Opportunity

We are looking for an exceptionally strong, hands-on Lead Software Engineer who thrives on solving difficult engineering problems at scale.

This is not a traditional people-management position. Approximately 80% of the role will remain hands-on coding, with the remaining 20% focused on technical leadership, architecture, strategy, mentoring, and customer-facing discussions.

You will initially work alongside a small, highly technical engineering team and have approximately one full-time direct report. Over time, this person will help expand the engineering organization and take increasing ownership of technical execution and leadership.

The ideal candidate is a builder at heart - someone who understands systems from the ground up, is comfortable working across multiple programming languages and technologies, and does not need to rely heavily on frameworks, third-party dependencies, or AI coding tools to solve complex problems.

• Spend approximately 80% of your time designing, building, testing, and shipping production software.
• Provide technical leadership and mentorship while remaining deeply involved in the codebase.
• Help architect systems capable of collecting, processing, indexing, and serving extremely large datasets - currently operating at approximately 50 TB of data per day.
• Expand the company's internet data collection capabilities, including dramatically increasing port coverage and the breadth of data collected across public internet infrastructure.
• Build scalable integrations and reusable integration patterns that allow the company to connect with additional data providers and customer environments out of the box.
• Help lay the technical foundation for incorporating AI and LLM capabilities into the company's data platform and workflows.
• Work across backend systems, APIs, infrastructure, data pipelines, and customer-facing product experiences.
• Contribute to UX/UI decisions and help ensure complex internet intelligence data is intuitive and useful to customers.
• Partner directly with customers to understand technical requirements, integrations, workflows, and product needs.
• Mentor engineers and help establish engineering standards as the team grows.
• Gradually take greater ownership of engineering execution, allowing company leadership to focus more heavily on strategy and growth.
• Help determine future architecture, tooling, engineering practices, and technical hiring priorities.

• 8-10+ years of professional software engineering experience preferred, although exceptional candidates with 5+ years of highly relevant experience may be considered.
• Demonstrated experience building complex, production-grade software systems - not simply integrating existing platforms and frameworks.
• Strong programming fundamentals with experience across multiple languages and technology stacks.
• Experience with languages such as Go, Rust, C, C++, Python, and/or Ruby.
• Strong understanding of APIs, distributed systems, networking, cloud infrastructure, data pipelines, and scalable system architecture.
• Experience working across multiple cloud environments or cloud-native architectures.
• Proven experience working with large-scale or high-throughput datasets.
• Ability to understand systems at a lower level and optimize for performance, scalability, reliability, and efficiency.
• Experience building products with minimal reliance on unnecessary third-party dependencies.
• Exposure to cybersecurity, internet infrastructure, networking, threat intelligence, DNS, scanning, or large-scale data collection is highly desirable.
• Experience with LLMs, AI-enabled products, or machine learning integrations is valuable.
• Enough frontend and UX/UI experience to contribute meaningfully to customer-facing product decisions.
• Experience interacting directly with customers and translating complex technical requirements into scalable product solutions.
• Previous experience within a startup or early-stage technology company is strongly preferred.
• Comfortable operating in an environment where engineers have significant ownership and problems may not have predefined solutions.