Software Engineer, Telnyx

• 3+ years of professional software development experience in Python
• Strong grasp of async Python frameworks (e.g. FastAPI, Starlette)
• Experience building and operating microservice-based systems
• Comfort working with relational databases at scale
• Solid understanding of distributed systems and production reliability
• Familiarity with LLM frameworks and tools (e.g. PyTorch, Transformers, DeepSpeed, vLLM), or strong experience building backend or platform systems that support ML workloads
• Excellent communication skills and the ability to work effectively across teams

Desirable

• Our Python teams build highly available, low-latency microservices using modern, cloud-native technologies
• This role sits within our broader AI organization and focuses on developing the platforms, services, and tooling that support AI-powered products — from inference and embeddings to APIs, data flows, and observability
• You’ll work in a fast-paced environment where reliability, performance, and usability matter just as much as innovation
• While some squads work closer to inference pipelines and LLM tooling, others focus on platform foundations, troubleshooting and reliability, data systems, or observability — all critical to delivering AI in production at scale
• Build, test, and deploy scalable Python microservices for AI-powered systems, including text and voice processing
• Design developer-friendly APIs and internal tools that make AI easy to use across the Telnyx product ecosystem
• Contribute to AI inference, embeddings, and platform services that support real-time and low-latency workloads
• Optimize performance, reliability, and observability in production environments
• Collaborate closely with Product, Infrastructure, and ML teams to bring features from ideation to production
• Troubleshoot, debug, and support critical systems running in production
• Participate in code reviews and uphold high engineering and operational standards
• Depending on the squad, your focus may lean more toward inference pipelines, platform foundations, observability, data systems, or production troubleshooting
• You’ll have the autonomy to take ownership of meaningful projects, contribute ideas that shape the product roadmap, and collaborate with talented people who care deeply about impact, quality, and long-term thinking

• We hire into a shared AI engineering pipeline. During interviews, we focus on core engineering skills, system design, and problem-solving ability. Final squad alignment happens later, based on:
• Your strengths and interests
• Team needs at the time
• Where you’ll have the biggest long-term impact
• This means the exact focus of the role may vary by squad, but the core expectation remains the same: building reliable, scalable AI systems in production