Principal Software Engineer

Two Six Technologies

10h•Remote

About The Position

Two Six Technologies is looking for an experienced Principal Software Engineer to join the Sigma product engineering team. You will be a key contributor to the evolution of this product, adding AI-powered features while using AI-assisted development techniques to maximize the speed at which we release features that are complete, resilient, and secure. It is an exciting opportunity to leverage the latest technologies to make a real-world impact. You should be comfortable taking on complex technical problems, dealing with ambiguity, forging technical strategies, crafting novel approaches to difficult challenges, and investigating and leveraging the latest AI tools to meet those objectives. Our small, remote team will give you the opportunity for outsized impact. As a Principal-level AI Software Engineer, you will actively participate in the design, build, test, implementation, and sustainment phases of product development, focused on advancing end-user operational outcomes while maintaining security and privacy. Your primary responsibility will be to leverage AI coding tools to build, test, and maintain the applications, services, APIs, and user interfaces that comprise this highly complex, multi-tier, AI-enabled software platform. To be considered for this role, you must have experience using AI coding tools to design, develop, test, and deploy features for a production application. The ideal candidate is both a strong, independent contributor, and a teammate; honesty, reliability, and trustworthiness are expected of everyone on the team. Sigma is a sensor-agnostic, mission-critical CBRNE SaaS platform built by Two Six Technologies, serving government and commercial users in radiological/nuclear detection. Our small, high-autonomy team ships production software using an agentic development model: engineers work alongside specialized AI agents for everything from architecture design to test generation to domain research. We are migrating from Java to Go on the backend, run multiple agentic AI stacks, and operate a structured knowledge system that keeps both humans and agents aligned. This is not a team where AI is a side project, it is how we build. Real product, real customers, real mission. This is a fully remote position with flexibility to manage your day around collaboration with your team.

Requirements

Bachelor’s degree in Computer Science, Engineering, or a related field, plus multiple years of professional software engineering experience. In lieu of degree, comparable experience will be considered.
Extensive experience writing production-level Go using AI-enabled tools and workflows
Practical experience using AI coding tools (e.g., Claude Code, Copilot, Cursor, or equivalent) to design, build, and test a mission-critical application that has run in production with an active user base.
Experience with large-scale (terabytes) database development, data modeling, mapping and testing. Must have Postgres and non-relational databases experience
Experience developing containerized applications using Docker and Kubernetes
Experience working with event-driven architecture
Practical experience designing, deploying, and tuning production systems running in AWS or a similar cloud computing environment
Experience with extracting, transforming, and loading (ETL) complex datasets
Experience finding and using open-source libraries where appropriate
Proficiency with automated unit, integration, and functional testing
Strong code review and troubleshooting instincts, catching subtle bugs, security issues, and design drift in both human- and agent-written code
Knowledge of which tools and technologies are currently best practice for a given problem, with the ability to consider solutions beyond those
Ability to work in a fully remote team with a diverse set of skills and life experiences
Ability to communicate ideas successfully, both verbally and in writing, with people at all levels of technical expertise, including non-technical colleagues
Ability to creatively solve problems and to learn quickly and independently

Nice To Haves

Experience with migrations from legacy systems to modern architectures (particularly Java to Go)
Experience with Java, Kafka, or Cassandra
Experience with CBRNE, defense/IC, or sensor-integration domains
Familiarity with protobuf/gRPC, Docker Compose, GitHub Actions CI/CD
Experience building or managing structured knowledge bases for AI agent consumption

Responsibilities

Actively participate in all phases of the software development lifecycle, regularly contributing code and reviewing code contributed by agents and the rest of the team
Design, build, test, implement, and maintain features, capabilities, and fixes, end-to-end (frontend, backend, and DevOps) within our agent-paired workflow
Develop full software stack features, applying UX principles to the UI, along with backend development, DB design, and AI integration
Stay current with the latest AI-powered software engineering technologies, evaluating them for the product and leveraging them wherever appropriate
Review and elevate AI agent output, critically evaluate code, specs, and analysis; catch what automation misses; enforce quality gates
Be a key contributor to the Java to Go migration, including shadow-mode validation, and contract testing between legacy and new services
Collaborate with Product Management and Customer Success to identify and address customer requirements, issues, and requests
Advise on the feasibility of technical requirements, schedule considerations, and potential risk for proposed new development work
Participate in building out, updating, and refining the product vision, plan, and roadmap
Leverage industry standards and best practices to regularly assess and address technical debt, particularly in consideration of cost-savings efforts and strategies
Collaborate with the DevOps team to implement, refine, and maintain infrastructure stability and availability, as well as continuous integration and deployment pipelines
Feed the structured knowledge base: distill decisions, designs, and trade-offs into agent-readable markdown so agents and teammates can reason about them
Follow TDD practices, writing tests before code as a default, not an afterthought
Mentor and learn from an experienced product development team