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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Software Engineer - **Company:** Telnyx - **Location:** United States (Remote available) - **Experience:** Expert - **Salary:** $208,000.0 - **Contract:** Permanent contract - **Skills:** JavaScript (Programming Language), Application Programming Interfaces (APIs), Agile Methodology, Artificial Intelligence, Amazon Web Services, Component-Based Software Engineering, Mobile Application Development, Cloud Computing, Code Review, Databases, Continuous Integration, Cursor, Github, Python (Programming Language), PostgreSQL, Machine Learning, Open Source Technology, Performance Tuning, Query Optimization, RabbitMQ, Next.js, Software Engineering, SQLAlchemy, TypeScript, Data Storage Technologies, ReactJS, Large Language Models, Claude Code, Snowflake, Multi-Agent Systems, AI Coding Agents, Backend, Git, Fastapi, Data Layers, Pytest, Kubernetes, Information Technology, Apache Kafka, Oracle Cloud Infrastructure, Docker, Jenkins, Crud - **Published:** October 27, 2026 - **Apply:** https://www.builtincolorado.com/job/senior-software-engineer-python/11895953?handler=ApplyRedirect ## About the Role * 5+ years of backend engineering, with strong production async Python. * You've owned systems that talk to many external services and lived with the async-job, retry, rollback, and eventual-consistency problems that creates. * You can make an LLM trustworthy in a real flow: validation, scoring thresholds, evals, audit, and human-in-the-escalation. You know where AI is reliable and where it's theater. * Postgres beyond ORM basics - you can read a plan, write a migration on a live system, and know why SKIP LOCKED matters. * You're a pragmatist about process automation - a workflow isn't done when the ticket closes, it's done when the human step is gone and the numbers prove it. * Strong written communication across a distributed team (EMEA + Americas). Bonus points for * Telecom/CPaaS background: DID inventory, ordering, porting (NPAC), carrier provisioning, regulatory/KYC familiarity. * Experience with document/KYC verification vendors (Onfido, Sumsub, Jumio) or OCR pipelines. * Building with agents beyond work: MCP servers, tool-calling frameworks, open-source agent runtimes. * Warehouse/analytics engineering; internal-dashboard work in TypeScript. ## Description We're looking for a senior engineer who lives at the seam between software, operations and AI. You've built systems where an order POST doesn't end at a database row - it ends at a carrier activating a real phone number in another country, subject to that country's rules. And increasingly, it ends with an AI agent deciding - reliably, auditable, in milliseconds - whether that order flows straight through or needs a human. You'll join the team that owns Telnyx's phone-number inventory and the entire ordering pipeline behind it. The stack is Python, the domain is global telephony, and the roadmap is near-total automation: if a step in the pipeline is done by a human today, we're building the system that takes that step away. What You'll Own * **The ordering pipeline** - async Python services that turn a search-and-order API call into a provisioned, billable phone number: job queues, retries, rollbacks on partial failure, SLA clocks, and backorder (advanced order) fulfillment where lead-time promises have contractual weight. Tens of thousands of orders a week run through this today. * **Vendor & carrier integrations** - dozens of them, from US Tier-1 wholesale carriers to international carriers and regulated-market vendors. Each integration is its own Snowflake - idiosyncratic APIs, failure modes, and regulatory constraints. You'll make them behave like one system. * **The AI order-review layer** - a production LLM service that reads orders and customer-submitted regulatory documents and auto-approves by country, number type, and carrier, governed by allowlists, score thresholds, and full audit logs. You'll own expanding its coverage safely: evals, guardrails, regression suites, and clean handoffs to humans when the machine isn't sure. * **Regulatory automation** - per-country identity/documentation checks ("requirement groups"), external document-verification vendors, expiry and re-verification flows - automated end-to-end in 45+ countries we hold carrier licences in. * **The data layer** - a large Postgres-based warehouse and Metabase analytics serving stock, SLA, and order-lifecycle dashboards used daily by ops and leadership, across a 30+ microservice estate; alerting on stock risk, vendor SLA breaches, and pipeline health. Tech stack (what you'll actually touch) * Python 3 (asyncio, FastAPI/aiohttp, SQLAlchemy, Alembic, pydantic), pytest, mypy/ruff * LLM tooling: model APIs, structured output, agent orchestration, prompt/scoring configuration, offline eval harnesses * PostgreSQL at scale: schema design, migrations on live systems, query tuning, warehouse SQL * RabbitMQ/Kafka, Consul, Kubernetes, Jenkins, Docker/OCI, GitHub Actions * Metabase, and TypeScript/Next.js for internal dashboards (not required - the backend is yours), * Not a pure CRUD role. Every row in this system is a real phone number somewhere - on a carrier, under a regulator, promised to a customer, watched by an SLA. * Not an ML research role. You'll build applied AI that approves real transactions - no notebooks in production, no fine-tuning required., Designs and builds scalable applications using React and Python, contributing to component development, data storage, deployment practices, performance optimization, testing, and client requirements analysis. The role collaborates with technical leaders, clients, and distributed teams in agile environments, using Git, code reviews, cloud platforms, databases, and AI-native development practices. U.S.-based travel to client sites is required., Evaluate AI coding agents such as Codex, Claude Code, and Cursor for engineering judgment, response quality, reasoning, explanations, and usefulness. Provide clear written and recorded feedback, distinguish quality levels, and help define standards for excellent AI-assisted development interactions. This contract role requires senior-level software engineering experience, strong Python or TypeScript/JavaScript skills, familiarity with modern AI development workflows, and excellent English communication. Top Skills: Claude CodeCursorJavaScriptLoomOpenai CodexPythonTypescript Houst Senior Software Engineer 15 Days Ago In-Office or Remote Georgia, USA 5K-6K Annually Senior level 5K-6K Annually Senior level Real Estate Build and operate Python backend services, APIs, and React frontends for a property-management platform. Use AI coding tools extensively for planning, implementation, reviews, testing, and evaluation. Own features end to end, integrate third-party platforms, maintain CI/CD and observability, support safe AWS releases, and collaborate with product and operations. Mentor teammates through code reviews and help establish effective AI-assisted engineering practices. Top Skills: AWSCircleCIClaude CodeCodexCursorDockerElastic StackFlaskGithub ActionsPostgresPython 3ReactReact NativeRedisSqlalchemy What you need to know about the Colorado Tech Scene With a business-friendly climate and research universities like CU Boulder and Colorado State, Colorado has made a name for itself as a startup ecosystem. The state boasts a skilled workforce and high quality of life thanks to its affordable housing, vibrant cultural scene and unparalleled opportunities for outdoor recreation. Colorado is also home to the National Renewable Energy Laboratory, helping cement its status as a hub for renewable energy innovation. Key Facts About Colorado Tech * Number of Tech Workers: 260,000; 8.5% of overall workforce (2024 CompTIA survey) * Major Tech Employers: Lockheed Martin, Century Link, Comcast, BAE Systems, Level 3 * Key Industries: Software, artificial intelligence, aerospace, e-commerce, fintech, healthtech * Funding Landscape: $4.9 billion in VC funding in 2024 (Pitchbook) * Notable Investors: Access Venture Partners, Ridgeline Ventures, Techstars, Blackhorn Ventures * Research Centers and Universities: Colorado School of Mines, University of Colorado Boulder, University of Denver, Colorado State University, Mesa Laboratory, Space Science Institute, National Center for Atmospheric Research, National Renewable Energy Laboratory, Gottlieb Institute