Senior Software Engineer, Team Lead

Your Mission

Cyberattacks are no longer just emails or random phone calls.

Voice phishing, deepfakes, and AI-generated social engineering are evolving fast, powered by the same AI breakthroughs we’re using to fight back.

Your mission is to lead the development of one of Hoxhunt’s largest and most business-critical product areas: our adaptive simulation training engine. It is used by over 4 million people globally.

This is the system that turns the latest threats into the right training moment for the right human automatically, reliably, and at massive scale.

Your Role

This role comes with clear ownership.

You are responsible for delivery in your product team and for turning product strategy into shipped outcomes. You keep scope focused, quality high, and momentum strong as complexity increases.

You shape the technical direction so the team can build a system that stays fast, reliable, and maintainable as scale and as AI complexity grow. This includes architectural choices that support long-term resilience rather than short-term heroics.

You raise the team’s AI engineering maturity. You help the team use modern AI tools in daily development, and you ensure AI-powered features are production-grade, measurable, and trusted.

You work closely with Product Management to shape the roadmap and keep the team focused on solving the real problem behind it, driving toward measurable behavior change.

You lead a product-focused engineering team by setting direction, raising standards, and supporting people’s growth while staying close enough to the work to remain grounded and credible.

What You’ll Do

• Lead delivery of large, ambiguous initiatives and turn strategy into shipped outcomes without sacrificing reliability.

• Set technical direction at scale and make pragmatic architecture decisions across data flows, event-driven systems, APIs, observability, reliability, and performance for a product used by millions - and the user is growing rapidly with the company growth.

• Work hands-on in our production stack using Node.js, TypeScript, React, GraphQL, MongoDB, and GCP to stay close to the system and the team.

• Build AI into both the product and the way the team ships, including adaptive simulations, reasoning layers, evaluation practices, feedback loops, monitoring, and guardrails.

• Partner closely with Product Management to shape priorities and ensure engineering effort translates into real-world behavior change.

• Act as a strong cross-functional link between engineering, product, and design, keeping alignment tight and trade-offs explicit.

• Raise the bar for the team by improving code quality, developing technical skills, and helping grow the team with the right competencies as the product scales.

What We’re Looking For

• Proven hands-on experience in a Tech Lead position or as an Engineering Manager with a small product team. You lead by building, not by abstraction.

• A strong track record of shipping and operating high-scale SaaS systems with real availability, latency, and data quality expectations.

• Full-stack technical competence across distributed and event-driven systems, APIs, and production operations including observability, incident response, and performance tuning.

• Strong product and engineering judgment. You can balance speed with sustainability and know when to simplify.

• Demonstrated ability to raise the bar through mentoring, setting standards, and building a delivery system that scales with the team.

• Practical, production-grade AI or LLM engineering experience, or strong evidence you can ramp up fast. You have shipped AI-driven capabilities with reliability, measurement, and safety in mind.

Bonus Points

• Experience with personalization or adaptive systems such as recommendations, optimization loops, segmentation, or risk scoring.

• Experience building agentic or reasoning-layer capabilities, including guardrails and evaluation practices.

• Familiarity with the security domain, including phishing, email ecosystems, threat intelligence, or abuse prevention.

• Experience scaling global user-facing systems with localization, multi-region considerations, or multi-tenant complexity.

The Real Challenges You’ll Tackle

• Keeping product and technical alignment tight as complexity and speed increase.

• Evolving an existing production codebase while shipping new AI-native capabilities.

• Staying ahead as tools, models, and scale pressures evolve faster than teams naturally can.

• Balancing experimentation with the expectations of a trusted, widely used global product.

• Resilience, curiosit