AI Native Software Engineer

Own and build core control-plane and telemetry experiences, from domain models, events, and APIs through the user-facing product
Translate distributed-system concepts such as state, dependencies, policy, identity, lineage, orchestration, failure, and recovery into clear product primitives and interactions
Develop workflows for agent-executed work, including intent expression, permission enforcement, activity observation, outcome explanation, auditing, and reversal
Create information-rich visualizations for state, change over time, relationships, anomalies, causality, and uncertainty
Decide what should be done by an agent, what requires human judgment, and what belongs in a graphical interface, API, or programmable surface
Define patterns for human oversight, review, exception escalation, and durable auditability
Prototype interaction models, test them against technical constraints, and bring strong ideas into production systems
Shape architecture and product direction through working software, technical judgment, and usability focus

Requirements

• Deep experience with data-intensive or distributed systems
• Experience building platform or control-plane software
• Experience directing multi-agent software development workflows
• Experience applying AI-native engineering practices, including specification-driven planning, implementation, review, and validation
• Exceptional product and information-design instincts
• Demonstrated ability to make high-dimensional, dynamic, or operational data understandable to humans
• Ability and willingness to work across the stack, including backend architecture, APIs, and user-facing experiences
• AI-native product judgment concerning agency, context, permissions, observability, evaluation, trust, and human control
• Nuanced understanding of human-in-the-loop design, risk, reversibility, uncertainty, accountability, and cost
• Comfort with ambiguity and first-principles product development
• Familiarity with databases, distributed compute, orchestration, telemetry systems, event models, observability, governance, security, or developer infrastructure is an advantage
• Experience with information visualization, operational analytics, investigative interfaces, or products involving complex changing data is an advantage
• Experience with enterprise or technical products where correctness, permissions, auditability, and operational safety matter is an advantage
• Experience with rich web applications or developer tools is an advantage
• Experience with AI agents, tool-using models, human-in-the-loop systems, or interfaces for planning and supervising automated work is an advantage
• Experience with zero-to-one product development is an advantage

Core Competencies

Demonstrates expertise in building control-plane and telemetry experiences, with a strong focus on data-intensive and distributed systems. Proficient in AI-native engineering practices and human-in-the-loop design, ensuring clarity and usability in complex data environments.

Highest-signal resume keywords

• Data-Intensive Systems
• Control-Plane Software Development
• AI-Native Engineering Practices
• Information Visualization
• Human-In-The-Loop Design

ATS Optimization Keywords

Hard Skills

• Distributed Systems
• Backend Architecture
• APIs
• Event Models
• Operational Analytics
• Complex Data Understanding
• Prototyping Interaction Models
• Multi-Agent Software Development
• Zero-To-One Product Development
• Telemetry Systems

Soft Skills

• Exceptional Product Design Instincts
• Comfort With Ambiguity
• Technical Judgment

Industry Keywords

• Auditability
• Operational Safety
• Human Control
• Trust
• Permissions

Tools & Technologies

• Databases
• Orchestration Tools
• Governance Systems
• Security Frameworks
• Developer Infrastructure