Senior Software Engineer (AI Software & Operations)

Surefire Cyber is redefining the incident response model by delivering a swifter, stronger response to cyber incidents. They are seeking a Senior Software Engineer (AI Software & Operations) to build greenfield applications in Python, own critical infrastructure, and ship production software across the full stack.

Responsibilities:

• 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
• 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

Requirements:

• 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