Member of Technical Staff - Backend/Platform

About APADCode APADCode is an early-stage AI startup building the infrastructure for a more meaningful way to evaluate software engineers. Our platform conducts live, adaptive technical interviews and captures how candidates approach problems, reason about trade-offs, write code, and respond to challenges. Behind the product is a two-engine architecture combining real-time AI interview orchestration with structured reasoning analysis. We've moved beyond prototypes into real hiring workflows. Now we're looking for engineers who want to help build the systems that will take us further. About the Role We're looking for a Member of Technical Staff to help own the architecture and evolution of APADCode's core backend platform. At the heart of our product is a stateful AI interviewer that needs to manage multi-stage technical conversations, coordinate live coding interactions, make context-aware decisions, and preserve a complete record of what happened. You’ll work on the engineering challenges behind making that experience reliable, responsive, secure, and scalable, while building the data infrastructure that powers our AI evaluation engine. This is a hands‑on role with significant architectural ownership and direct collaboration with the founding team. What You’ll Work On Real‑time interview orchestration: Design and evolve the stateful runtime powering our Interview Control Engine, including interview stages, transitions, time budgets, and session lifecycle management. AI agent coordination: Build the orchestration layer connecting live conversation, lightweight reasoning classifiers, adaptive follow‑up decisions, and coding permissions. Handle model latency, failures, retries, and inconsistent outputs gracefully. Event‑driven architecture: Develop reliable event capture for candidate responses, interviewer actions, stage transitions, code revisions, and execution results. Preserve event ordering and data integrity for downstream evaluation. Coding execution infrastructure: Improve the backend supporting our interactive coding environment, including execution isolation, resource limits, timeouts, and secure handling of untrusted code. Asynchronous processing: Design pipelines that move raw interview events into the Cognitive Intelligence Engine for normalization, feature extraction, and evaluation. Reliability and observability: Build instrumentation around session failures, agent latency, execution errors, processing delays, and infrastructure costs. Improve recovery behavior and production visibility. Platform foundations: Shape service boundaries, database architecture, APIs, deployment workflows, multi‑tenant isolation, and security practices as the platform grows. What We Look For Strong experience designing, building, and operating SaaS production backend systems. Deep understanding of concurrency, asynchronous workflows, state management, distributed systems, and failure recovery. Proficiency in a backend language such as Python, Go, or TypeScript. Experience with relational databases, caching, queues, and event‑driven architectures. Practical experience with cloud infrastructure, containerization, CI/CD, and production observability. Ability to make sound engineering trade‑offs around latency, consistency, reliability, complexity, and cost. Comfortable taking ambiguous technical problems from architecture through implementation and production operation. Nice to Have Experience with LLM agents, tool calling, or workflow orchestration (not in demo, but in production system of Enterprise). Experience building WebSocket‑based or other low‑latency interactive applications. Familiarity with sandboxed code execution, container isolation, or resource‑constrained workloads. Experience with technologies such as PostgreSQL, Redis, Kafka, Kubernetes, or comparable systems. What We Offer Competitive compensation and meaningful early‑stage equity opportunities. Significant architectural ownership and influence over technical direction. Direct collaboration with the founders and a small engineering team. Flexible working arrangements, paid time off, and health benefits based on location. Equipment and professional development support. The opportunity to build foundational AI infrastructure for hiring v3.0 We're looking for engineers who enjoy owning complex systems, making thoughtful technical decisions, and shipping software that holds up in production. #J-18808-Ljbffr APADCode