Senior Software Engineer (AI Software & Operations)

Design and implement services, RESTful and event-driven APIs, and data access layers across Python backends and React frontends

Contribute to integration between internal services and external platforms, including third-party APIs relevant to IR workflows and business operations

Write code that other engineers can read, extend, and trust in production

Own and operate AWS infrastructure across all environments (dev, staging, production), including Kubernetes, Terraform, and CI/CD via GitHub Actions. Engineers here own what they ship, from code to infrastructure — that’s a feature, not a burden

Build monitoring, alerting, and observability so production issues surface early and resolve fast

Ensure infrastructure aligns with Surefire’s security and compliance requirements. We’re a cybersecurity company; security is a design constraint, not a review step

Identify weaknesses in the current architecture and propose pragmatic improvements with clear rationale

You have code in production by the end of your first sprint. Within 30 days, you have a working mental model of the environment and have started closing the highest-leverage gaps. You ship consistently, ask good questions, and make the systems around you better every week.

Strong software engineering fundamentals: writing, debugging, and reasoning about code independently of AI tooling, with a track record of building, not just maintaining

Full-stack capability across backend (Python, API design, relational and non-relational databases) and frontend (React or equivalent)

Production-level AWS experience, including VPC design, EC2/ECS/Lambda, IAM, RDS, S3, and Kubernetes

Terraform proficiency as a primary tool, not a secondary skill

GitHub Actions or equivalent CI/CD pipeline experience at a production scale

Comfort operating with significant autonomy on a small team where you ship fast, handle ambiguity, and self-enforce process

Willingness to work beyond normal business hours to meet business demands, as needed

Hands-on experience building or operating AI agent workflows using tools such as Claude Code, LangChain, AutoGen, CrewAI, or equivalent

Familiarity with MCP (Model Context Protocol) server architecture and LLM context injection patterns

Background in cybersecurity, incident response, or compliance-adjacent engineering environments

Experience at a startup or high-growth environment where moving quickly, wearing multiple hats, and operating without a large support structure is the norm

Expertise in all these areas is not required, but you should be excited by the opportunity to learn new things and comfortable working with other team members to expand your knowledge base and experience. We at Surefire Cyber invite you to apply even if you do not feel you have mastery in all the requirements listed on the job description and welcome a further discussion.

Submit interest to job posting

Preliminary phone interview with the Surefire Cyber People Team (approx. 30 minutes)

Virtual interview with the hiring manager (approx. 30-45 minutes)

Technical pairing session with a member of the engineering team (approx. 60 minutes)

Virtual interview with cross-functional stakeholders (approx. 45 minutes)

Virtual interview with the Chief Executive Officer (CEO) (approx. 30 minutes)