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 (strongly preferred)
Familiarity with MCP (Model Context Protocol) server architecture and LLM context injection patterns (strongly preferred)
Background in cybersecurity, incident response, or compliance-adjacent engineering environments (strongly preferred)
Experience at a startup or high-growth environment where moving quickly, wearing multiple hats, and operating without a large support structure is the norm (strongly preferred).
Tech Stack
AWS
Cyber Security
EC2
Kubernetes
Python
React
Terraform
Benefits
Competitive compensation plan and total rewards package for team members
Remote workforce
Generous paid time off plan and floating holidays
Paid parental leave
Employer paid premiums for both team members and their dependents for medical, dental, and vision
Comprehensive health, vision, dental, 401K matching program, disability, Flexible Spending Accounts (FSA), Health Savings Account (HSA), Life and AD&D benefits.
Professional development and career advancement opportunities
We prioritize employee growth and development through a robust performance management platform to provide ongoing coaching, clear feedback, recognition, and opportunities for career growth.