Nir Yu

Lead full technical stack development and set architectural direction for AI platform with real-time voice and cloud infrastructure. | Staff-level engineer with 4+ years in production systems, deep cloud infrastructure expertise, proficiency in Python, FastAPI, TypeScript, and preferably voice AI or telephony experience. | The Role: You own the stack and set technical direction alongside the founders. You have a real say in the big architectural decisions, and what you ship reaches real users quickly. Perform well and you're on track to Lead Engineer. Responsibilities: Own features end to end across frontend, backend, and the infrastructure they run on. Build and scale our AI employees platform: the application, the FastAPI services, and the data flows that connect them. Run our cloud and telephony backbone on GCP and Kubernetes, keeping production reliable and low-latency as we grow. Lead our real-time voice work and own its hardest challenges: pushing the voice to be the most realistic, driving down latency, and expanding what our AI employee platform can do. Set technical direction with the founders and raise the engineering bar as the team grows. Requirements: You own systems end to end, you have deep cloud infrastructure experience at the staff level, and you use AI in your own work every day. You don't need deep voice, telecom, and applied AI all on day one. Our stack is Python and FastAPI on the backend, GCP and Kubernetes for infrastructure, a modern TypeScript frontend, and real-time media on top. You should be comfortable across most of it and strong in at least one layer. Great to Have: Experience at a voice AI, speech, or telephony company (TTS, STT, SIP, VoIP, latency optimization), or running Kubernetes in production at an early-stage company. Ideal Profiles: Staff or senior full-stack engineer with 4+ years shipping production systems, who has owned cloud infrastructure at scale, ideally with voice, SMS, or real-time media experience. Engineer building with applied AI beyond prompt engineering (speech models, ML pipelines, real-time inference) who wants to do it full time. Engineer from a voice, telephony, or legal-tech company who already knows the real-time stack and the integration landscape.

Provide bilingual technical support by triaging and resolving issues across phone, email, and SMS workflows, debugging full stack using logs and APIs to improve product quality. | Requires 2+ years technical customer-facing experience, proficiency in Python, full fluency in English and Spanish, and comfort with APIs, SQL, and logs. | The Role: You are the technical front line for our AI employees in production. You debug real issues across the stack, talk directly to firms and their clients in English and Spanish, and turn what you learn into fixes and product improvements. Your work is visible to the founders and reaches real users immediately. Responsibilities: • Own support for our AI employees in production: triage, reproduce, and resolve issues across phone, email, and SMS workflows. • Debug across the stack: read logs, query APIs, write scripts, and trace calls through our FastAPI services, escalating true platform bugs with clear, reproducible reports. • Provide bilingual support (Spanish and English) to firms and the clients our AI employees speak with. • Configure and tune AI employees per firm: intake scripts, routing, case-management integrations, and Spanish-language conversation quality. • Build tools, runbooks, and automations that make support faster and turn recurring issues into permanent fixes, feeding patterns back to product. Requirements: • Support or solutions engineer with 2+ years in a technical, customer-facing role who can code (Python or similar). • Fully fluent in Spanish and English, written and spoken, supporting both clients and internal teams in either language. • Comfortable with APIs, logs, SQL, and the command line; bonus for telephony, SMS, or real-time voice experience. • Background in legal tech, a law firm, or another regulated, client-heavy environment is a plus. Who You Are: You are technical and hands-on, fluent in both Spanish and English, and you like solving problems for real people. You can read code and write scripts to investigate issues, and you stay calm and clear when a firm needs help fast. Our stack is Python and FastAPI, GCP and Kubernetes, a modern TypeScript frontend, and real-time media on top. You don't need to master all of it, but you should be comfortable reading code, calling APIs, and digging into logs to find root cause.

Lead engineering team to support backend architecture and data pipelines with scalable cloud solutions. | Strong technical expertise in .NET, Spark/Databricks, Azure DevOps, and leadership experience in production environments. | The Role: We’re seeking a hands-on Engineering Team Lead to design and deliver scalable backend services and data platforms within a distributed, event-driven architecture. This role blends technical leadership with system ownership and requires strong expertise in Databricks, .NET, data processing, and Azure-based Cloud/DevOps practices. The Team Lead will oversee daily support for Client’s Product Master and Vendor Master systems built on EBX, SSIS/ADF, SQL Server, ASP.NET, Azure, and on-prem environments. The role also includes hands-on development—delivering enhancements to legacy systems and designing and coding solutions in Databricks. Key Responsibilities: Lead a team of Engineers to Support Product Master and Vendor Master day to day tickets, and patching + upgrades Own architecture across backend services, SQL/data models, and data pipelines Lead design and delivery of ASP.Net/.Net and REST APIs Hands on develop solutions using Databricks Ensure system reliability via monitoring, observability, and performance tuning Guide team on best practices in backend, data, and distributed systems Collaborate with stakeholders to align technical solutions with business needs Improve CI/CD pipelines and cloud infrastructure Requirements: Data Experience with Spark / Databricks Handling large-scale data processing (batch/streaming) ( SSIS/ADF/Kafka/Service Bus/Event Hub) Backend Strong experience with .Net /ASP.Net Solid experience with REST APIs, microservices, and distributed systems Strong knowledge of SQL, relational databases, and data modeling DevOps / Cloud Experience with Azure Hands-on with CI/CD pipelines (Azure, GitHub Actions) Experience with monitoring/observability tools (e.g., Datadog) Familiarity with containers and orchestration concepts Leadership Experience leading teams or driving technical initiatives Strong ownership of production systems and delivery Nice to Have: Experience with event-driven systems (Kafka or similar) Experience with large-scale data platforms Knowledge of GraphQL APIs Experience modernizing legacy systems Must Have: Hands-on technical leader Strong ability to own and debug systems in production end-to-end Comfortable across backend + data + cloud layers Experience building scalable, high-performance systems Ability to mentor engineers while contributing technically

Develop and maintain backend services, support Java-based systems, architect GCP solutions, and mentor engineers. | 5+ years backend experience, proficiency in Python and Java, GCP expertise, experience with data-intensive applications, and ownership of services. | Responsibilities: Develop and maintain critical backend services and APIs, primarily using Python (e.g., Flask, FastAPI). Support, maintain, and contribute to existing Java-based services and libraries (e.g., Spring Boot), demonstrating polyglot flexibility. Architect cloud-native solutions that are built to run on Google Cloud Platform (GCP), leveraging GKE, Pub/Sub, and BigQuery. Design and optimize data-intensive applications that interface with large-scale data stores, including BigQuery. Lead technical design discussions, write detailed design documents, and mentor junior engineers on the team. Drive continuous improvements in system architecture, reliability, performance, and CI/CD processes. Own services end-to-end, including monitoring (DataDog, etc.), setting SLOs, and participating in on-call rotations. Requirements: 5+ years of professional backend engineering experience. Expert-level proficiency in Python for backend development and data-intensive applications. Professional experience with Java (e.g., Spring Boot) and a willingness to work in a polyglot environment. Proven, deep hands-on experience designing and operating solutions on Google Cloud Platform (GCP), with production expertise in Google Kubernetes Engine (GKE), BigQuery, and Pub/Sub. Experience with event-driven architectures, DDD, and TDD. Experience with big data technologies (Spark, Kafka) and integrating ML models is a strong plus. Experience with large-scale data stores, including relational databases and data warehouses like BigQuery. A strong sense of ownership and a drive for technical excellence. Experience leveraging modern IDEs and AI-assisted development tools (e.g., Cursor, GitHub Copilot) to accelerate development cycles.