Raynmaker Inc-posted 5 days ago
Full-time • Mid Level
Austin, TX

Raynmaker.ai is the AI-native sales engine purpose-built for small and mid-sized businesses. We empower local and franchise businesses to compete with enterprise-level capabilities—through AI-driven lead targeting, next-best-action automation, and intuitive workflows that help them close more deals, faster. We're a venture-backed, fast-growing team committed to helping SMBs grow with confidence. We’re looking for a Senior Full Stack Python Engineer to lead the development and operation of the core real-time services behind our autonomous AI-driven sales platform. You will architect, build, and maintain production-grade systems that power voice, chat, scheduling, payments, and other mission-critical workflows used by real businesses every day. This is a hands-on, high-impact role where you will work directly with technology leadership, own major components of the platform, and help scale a modern cloud-native environment that integrates AI, real-time communication, and multi-tenant SaaS infrastructure. If you thrive in complex distributed systems, enjoy building high-performing services end-to-end, and want to help shape the backbone of an AI-first company, this role is for you.

  • Architect, build, and operate Python/FastAPI microservices that power real-time customer interactions.
  • Develop scalable, event-driven systems for voice, chat, scheduling, payments, and other operational flows
  • Own end-to-end production services including availability, performance, reliability, and observability.
  • Build and maintain large-scale, multi-tenant data pipelines supporting both transactional and ML-driven use cases.
  • Build high-quality front-end experiences using React and TypeScript.
  • Create internal dashboards, configuration tools, and admin consoles for platform operations.
  • Integrate real-time UI elements using WebSockets, streaming APIs, and live data updates.
  • Design and operate distributed systems with a focus on real-time performance (voice, streaming, WebSockets).
  • Implement event-driven workflows using Kafka, Kinesis, SQS, or similar technologies.
  • Deploy, scale, and monitor workloads on AWS (EKS, EC2, ALB, IAM, VPC, RDS, S3).
  • Use Kubernetes and Docker for container orchestration and service reliability.
  • Work alongside ML teams to expose LLM- and RAG-powered services into production systems.
  • Integrate with vector databases, agent frameworks, and LangChain/LangGraph pipelines.
  • Build API endpoints and backend flows that leverage AI capabilities safely and efficiently.
  • Participate in on-call rotations and lead incident response for platform services.
  • Implement strong observability: logs, metrics, tracing, dashboards, alerts.
  • Own release management, versioning, CI/CD workflows, and deployment automation.
  • Continuously improve system reliability, performance, and scalability.
  • 10+ years of professional software engineering experience.
  • Expert-level Python engineering skills.
  • Expert-level TypeScript and React full stack development experience.
  • Deep experience with FastAPI and microservices architecture.
  • Strong background in distributed systems and large-scale pipelines.
  • Real-time systems expertise: voice, streaming, WebSockets, live event flows.
  • Exposure to the modern AI stack (RAG, vector DBs, LLMs, LangChain/LangGraph).
  • Experience building multi-tenant SaaS platforms.
  • Strong understanding of event-driven systems (Kafka, Kinesis, SQS).
  • AWS cloud experience: EKS, EC2, ALB, IAM, RDS, S3, VPC.
  • Proficiency with Kubernetes & Docker.
  • Experience with observability tooling and incident response.
  • Strong SQL and NoSQL database fundamentals.
  • Experience with third-party integrations (Stripe, Calendars, Toast, POS/CRM systems).
  • Security foundations: OAuth, JWT, RBAC, secure API design.
  • Experience operationalizing AI systems in production.
  • Startup or rapid-growth company experience.
  • Infrastructure-as-Code (Terraform) experience.
  • Building/maintaining modern CI/CD pipelines.
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