Senior Software Engineer (AI Software & Operations)
About Surefire Cyber
Surefire Cyber is redefining the incident response model by delivering a swifter, stronger response to cyber incidents such as ransomware, email compromise, malware, data theft, and other threats. Our client-centric approach reduces stress and provides clients the confidence needed to prepare, respond, and recover from cyber incidents – and fortify their cyber resilience after an event.
Surefire Cyber’s approach and delivery are designed by industry veterans who have worked shoulder-toshoulder with law firms, insurance carriers, brokers, law enforcement, and impacted organizations in responding to cyber incidents. We are marshaling this experience to address the industry’s persistent challenges of efficiency, predictability, and transparency
How You’ll Make An Impact
Surefire Cyber is looking for a Senior Software Engineer (AI Software and Ops) to build greenfield applications in Python using agentic methods, own critical infrastructure, and ship production software across the full stack. Reporting to the Head of Engineering, you will write code, make architecture calls, and operate the systems you build. This is a startup, and the right person thrives in ambiguity, prototypes fast, iterates in tight loops, and ships working software every sprint.
The right person is a full-stack generalist who writes production-quality code, has strong opinions on how to build and run infrastructure, and is genuinely excited about what agentic AI makes possible. You will work across the entire engineering surface: Python backends, React frontends, AWS infrastructure, CI/CD pipelines, and AI-driven workflows. Surefire is AI-native by design, and you will operate with the teamwork, tenacity, and empathy that define how we work.
You will serve as an individual contributor across engineering projects in flight, including support of existing Python/React applications in active use by customers and new builds. The team operates on a 2-week sprint cadence.
Your Role In Action
Agentic Engineering and AI-First Systems
- Build greenfield Python applications using agentic methods, including AI agent workflows with tools such as Claude Code, LangChain, or equivalent frameworks
- Architect the scaffold layer that coordinates multi-agent pipelines, including role separation, context injection, and output validation
- Integrate agentic systems with the GitHub-based knowledge store that serves as the org-wide context layer for engineering work
- Evaluate and adopt new agentic tooling and LLM capabilities as they emerge, bringing structured recommendations to the team
Full-Stack Development, APIs, and Integration
- 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
Infrastructure, DevOps, and Security
- 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
What Success Looks Like
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.
Your Expertise
Required
- 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
Strongly Preferred
- 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.
Interview Process
- Submit interest to job posting or send to careers@surefirecyber.com
- 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)
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