Director of Software Engineering

Coreforce•Atlanta, GA

2d•$180,000 - $220,000•Hybrid

About The Position

Apply today to join Coreforce, where your Engineering expertise makes a real impact. Join Our Team as a Director of Software Engineering Company: Coreforce Location: Atlanta, GA Job Type: Full-time Salary: Based on Experience Company Overview: Coreforce is an innovative technology company providing public safety organizations a comprehensive technology suite from dispatch to the courtroom. Coreforce delivers integrated technology designed to support public safety entities, regardless of organizational size. Our products - body cameras, in-car videos, mobile routers, and digital evidence systems- help public safety officers and first responders save lives, strengthen community trust, and enhance accountability. Director, Software Engineering - Build Your Career with Purpose Join Coreforce and use your engineering skills to support innovative technology that strengthens communities.

Requirements

Significant experience in software engineering leadership — directly managing engineers while remaining an active hands-on contributor.
Strong proficiency across the full stack — actively writing production code in Java (Spring Boot), TypeScript (Vue/React), and Python; not just reviewing or advising.
Deep hands-on experience with AWS (or Azure) — compute (ECS, Lambda), storage (S3, RDS, DynamoDB), messaging (SNS/SQS, EventBridge, Kafka), networking, and deployment patterns.
Experience designing and operating event-driven architectures using Kafka and/or cloudnative messaging (SNS/SQS, EventBridge) — including topic design, consumer group management, schema evolution, dead-letter handling, and observability.
Demonstrated AI-first mindset — personally uses AI tools (coding assistants, LLMs, automation) daily in development workflows and has experience driving AI adoption across a team.
Proven ability to make architecture decisions that scale — microservices, event-driven systems, serverless patterns, data modeling (SQL and NoSQL), and API design in production environments.
Experience owning quality outcomes — not just delegating to QA but integrating quality engineering into team structure, sprint workflow, CI/CD, and release processes.
Proven ability to hire, develop, and retain strong engineering talent across both software engineering and quality engineering disciplines.
Track record of delivering software in agile/Scrum environments — sprint planning, backlog management, release cadence, and continuous delivery.
Experience managing technical debt alongside feature delivery — making informed investment decisions that balance velocity with long-term platform health.
Strong understanding of non-functional quality dimensions — performance engineering, accessibility (WCAG), security testing, and reliability/SLO management.
Experience with CI/CD pipeline strategy, test automation architecture, and release engineering practices.
Excellent communication skills — able to translate between engineering details and business/product language, report clearly to executives, and give direct feedback to reports.
Experience driving operational excellence — incident management, production monitoring, SLOs, and post-incident processes.

Nice To Haves

Experience leading teams building public-safety, law enforcement, or mission-critical software systems with high reliability and compliance requirements.
Experience building AI/LLM-powered product features — RAG, multi-agent workflows, computer vision, or intelligent automation — in production systems.
Track record of transforming a team's engineering practices through AI adoption — measurably improving velocity, quality, or capability through AI-first workflows.
Background in evidence management, chain-of-custody workflows, or regulated data handling.
Experience managing teams that own both web application delivery and physical device software/integration testing.
Background with compliance frameworks (FedRAMP, CJIS, SOC2) and how they impact engineering practices.
Experience with multi-tenant SaaS platform architecture and the engineering tradeoffs involved.
Track record building quality engineering practices from the ground up — establishing test automation, non-functional testing programs, and release quality standards for a growing org.
Experience managing distributed or hybrid-remote engineering teams.
Prior track record as a Staff or Principal-level IC — demonstrating the technical depth expected of someone who leads and contributes simultaneously.

Responsibilities

Directly manage a team of Software Engineers and Quality Engineers — owning hiring, career growth, performance management, and day-to-day technical leadership.
Own team health and performance — career growth conversations, performance management, succession planning, and building a culture of psychological safety and engineering excellence.
Partner with product management to translate roadmap into technical strategy, sequence work effectively, and communicate tradeoffs between scope, quality, and timeline.
Represent your team's technical capabilities and capacity to executive leadership — providing clear, honest reporting on progress, risks, and resource needs.
Define and maintain hiring standards — conducting interviews, calibrating levels, and building a pipeline of strong engineering and quality talent.
Champion engineering culture — continuous improvement, knowledge sharing, design reviews, blameless retrospectives, and cross-team collaboration.
Coordinate dependencies between your team and other engineering teams (firmware, hardware, platform, DevOps) to deliver integrated product outcomes.
Contribute directly to the codebase every sprint — designing and implementing critical features, services, and infrastructure in Java (Spring Boot), TypeScript (Vue/React), and Python.
Conduct code reviews regularly — maintaining high standards for quality, security, and maintainability across the team's output.
Debug and resolve complex production issues — working directly in the code and infrastructure to diagnose root causes and implement fixes.
Own operational excellence for your services — incident response, SLOs/SLAs, production monitoring, and post-incident review processes.
Personally use AI tools daily to accelerate development, design reviews, code generation, documentation, debugging, and decision-making — modeling the AI-first behavior expected of the team.
Own quality holistically — ensuring functional, non-functional (performance, accessibility, security, reliability), and operational testing are embedded in the delivery lifecycle, not bolted on after.
Drive architectural decisions at the product/team level — microservices decomposition, event-driven architecture (Kafka, SNS/SQS, EventBridge), serverless adoption, data storage strategy (SQL and NoSQL), and API design.
Design and evolve event-driven systems using Kafka and AWS messaging services — defining topic strategy, consumer patterns, schema governance, and ensuring reliable, ordered processing for critical workflows.
Set engineering standards and practices for your team — including code quality, testing strategy, CI/CD practices, architecture review processes, and release criteria.
Drive an AI-first engineering strategy — identifying opportunities to integrate AI/LLM capabilities into products, development workflows, testing practices, and operational tooling.
Manage technical debt strategically — balancing feature delivery with investment in platform reliability, test infrastructure, developer experience, and operational tooling.
Own delivery outcomes for your product area — ensuring architectural choices support shipping features on time, at quality, and aligned with product and business goals.