Senior Software Engineer (Platform Continuity)

Senior Software Engineer (Platform Continuity) 
Reports to: Co-Founder / CPO 
Day-to-day Partner: Lead Architect 
Department: Product & Engineering 
Location: Remote (US) 
Company Stage: Venture-backed AI company (Seed to Series A) 
Salary: $180-200k, + equity 
Location: Remote 

Role Overview 
Iridius provides the execution layer for compliant AI in regulated industries, turning regulatory standards into executable logic so evidence is generated continuously as systems run. We are seeking a Senior Software Engineer to join the platform team and partner closely with the Lead Architect. This is a hands-on build role with a structured shadowing and learning ramp. In the first months, you will work side-by-side with the Lead Architect across the platform, vendor pods, and AI initiatives, absorbing context and contributing production code from day one. Over time, you will take on increasing independent ownership and provide bench coverage during the Lead Architect's planned short absences, with full handoff support. This role is a strong fit for an experienced engineer who wants to grow inside an AI startup: learning cloud-native platform delivery, agentic AI patterns, regulated-industry compliance, and multi-vendor delivery models, while contributing meaningfully from week one. 

Scope of the Role & Core Responsibilities 
•    Platform Engineering: Build and maintain core platform services alongside the Lead Architect. 
•    AI-Augmented Engineering: Use AI tools across the SDLC and learn emerging agentic patterns. 
•    Vendor Pod Collaboration: Work as a peer reviewer and contributor with distributed contractor pods, under the Lead Architect's governance. 
•    Shadowing, Coverage, and Growth: Shadow the Lead Architect, build full-stack platform context, and provide coverage during planned short absences. 
•    Core Responsibilities Platform Engineering 
•    Build and evolve core Iridius platform services using Python, Kubernetes, and event driven cloud-native architectures on Azure. 
•    Implement production-grade backend services that meet standards for reliability, security, scalability, observability, and maintainability. 
•    Contribute to features supporting traceability, validation, auditability, and evidence generation for regulated customers.
•    Follow architectural direction set by the Lead Architect, raising questions and proposing improvements as understanding grows. AI-Augmented Engineering 
•    Work within an AI-augmented engineering workflow using tools such as Claude Code, GitHub Copilot, Cursor, or similar systems for development, testing, debugging, refactoring, documentation, and review. 
•    Apply engineering judgment to validate AI-generated outputs for correctness, security, maintainability, and architectural fit. 
•    Learn and apply emerging AI engineering patterns including multi-agent systems, retrieval-augmented systems, vector databases, and knowledge graphs. 
•    Contribute to evaluation, monitoring, and guardrail practices for AI-enabled features. Vendor Pod Collaboration 
•    Collaborate with distributed contractor pods on shared deliverables as a peer engineer. 
•    Provide code review and quality feedback within assigned scope. 
•    Surface delivery risks, quality gaps, or technical ambiguity early to the Lead Architect. 
•    Vendor governance, contractual oversight, and final acceptance remain with the Lead Architect. Shadowing, Coverage, and Growth 
•    Shadow the Lead Architect across services, vendor interactions, and architectural decisions to build full platform context. 
•    Provide partial coverage during the Lead Architect's planned short absences, with documented handoff and clear escalation paths. 
•    Maintain continuity on critical-path items and unblock vendor pods on routine technical questions. 
•    Grow into expanded architectural, AI, and technical leadership scope over time as judgment and context develop. 
What Success Looks Like in 6 Months 
•    Confidently navigates and modifies any of the platform's microservices. 
•    Ships production features independently within the architectural direction set by the Lead Architect. 
•    Provides effective coverage during the Lead Architect's short absences without slippage on critical work. 
•    Trusted second reviewer on vendor PRs and design decisions. 
•    Demonstrated growth in agentic AI patterns and regulated-industry delivery practices. 

Who We're Looking For You are an experienced engineer who values learning as much as shipping. You are comfortable spending the first months in a shadowing and partnership mode, contributing code from day one while building the context needed to take on broader ownership. You bring strong fundamentals, humility, curiosity, and the maturity to ask before assuming. 

Core Qualifications 
•    8+ years total, with 5+ years building production cloud-native services in Python on Azure, and hands-on use of AI-assisted development tools.
•    Expert proficiency in Python and working knowledge of at least one additional language. 
•    Strong cloud-native development experience: APIs, container-based architectures, observability, and CI/CD (Azure preferred). 
•    Comfortable deploying and operating application services on Kubernetes. 
•    Fluent with AI-assisted development tools and able to critically evaluate their outputs. 
•    Strong software quality practices: automated testing, code review, secure development, maintainability, and production readiness. 
•    Familiarity with DevSecOps and secure SDLC practices. 
•    Relational database design; familiarity with vector, graph, or other modern data approaches is a plus. 
•    Strong written and verbal communication. 
•    Comfortable in ambiguous, fast-moving environments, and excited to learn quickly inside an AI startup. Helpful Experience 
•    Exposure to multi-agent systems, agent orchestration, retrieval-augmented generation, vector databases, or knowledge graphs. 
•    Experience in regulated industries such as pharma, life sciences, healthcare, finance, government, aerospace, or other high-trust environments. 
•    Experience working with distributed engineering teams or contractor pods as a peer contributor. 
•    Azure, Azure DevOps, Kubernetes, event-driven architectures, infrastructure-ascode, and production observability. 
•    Exposure to Responsible AI, AI governance, compliance automation, auditability, traceability, or evidence-generation systems.