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Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in software engineering with a strong foundation in software architecture and testing practices, particularly in the context of AI coding agents. Capable of producing precise technical specifications and maintaining high-quality standards in regulated environments.
Highest-signal resume keywords
Software Engineering ExperienceAI Coding Agents ProficiencySoftware Architecture KnowledgeTechnical Specification DevelopmentRegulated Software Delivery Knowledge
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Software EngineeringSoftware ArchitectureTesting PracticesTechnical Specification DevelopmentPythonSQLJavaScriptTypeScriptCI/CD PipelinesML Model Deployment
Soft Skills
Results-Oriented ApproachCritical EvaluationAccountability for Quality
Tools & Technologies
AWSAzureKubernetesAGENTS.mdLintersFitness TestsVerification LoopsLLM-as-Judge Reviewers
Industry Keywords
DecisioningCredit RiskFraud DetectionAnalyticsOptimisationData EngineeringControlled Change Management
Tech Stack
Tools & technologiesAWSAzureJavaScriptKubernetesPythonSQLTypeScript
About the role
Key responsibilities & impact- Collaborate with Product teams to translate early-stage ideation into structured Proofs of Concept
- Establish clear technical feasibility and scope
- Produce detailed specifications and acceptance criteria for coding agents
- Own resulting code through deployment
- Apply rigorous quality standards to agent-generated output in a regulated decisioning context
- Operate within the agentic harness using AGENTS.md files, architectural rules, reference documentation, linters, fitness tests, verification loops, and LLM-as-judge reviewers
- Identify root causes of recurring agent errors
- Work with the harness team to implement systemic controls
- Maintain accurate and current repository documentation, specifications, and contextual knowledge
- Apply technical judgment to architecture decisions, edge-case analysis, latency and integration risk, auditability, and agent-autonomy boundaries
Requirements
What you’ll need- Demonstrable experience in software engineering within large, complex codebases
- Strong foundation in software architecture, testing practices, and long-term maintainability
- Practical experience with AI coding agents such as Claude Code, GitHub Copilot, Codex, or Cursor
- Understanding of AI coding agents’ capabilities, limitations, and appropriate production use
- Ability to critically evaluate agent-generated output and identify subtle errors or architectural weaknesses
- Ability to produce precise, unambiguous, testable, and actionable technical specifications and definitions of done
- Disciplined approach to verification, checks, and test coverage
- Results-oriented approach with accountability for quality and correctness of shipped work
- Familiarity with Python, SQL, JavaScript/TypeScript, AWS or Azure, Kubernetes, CI/CD pipelines, ML model deployment, or real-time decisioning systems
- Experience with spec-driven development, context engineering, or agent orchestration is a significant advantage
- Knowledge of regulated or audited software delivery processes and controlled change management is advantageous
- Background in decisioning, credit risk, fraud detection, analytics, optimisation, or data engineering is advantageous
- Ability to articulate human-AI collaboration, delegation boundaries, human oversight, and earning autonomy through demonstrated quality
Benefits
Comp & perks- Highly competitive compensation, benefits and rewards programs
- Work/life balance
- Employee resource groups
- Social events
- Professional development and valuable learning experiences
- Inclusive, people-first work environment
- Freedom to develop skills and grow your career