Hiring: Software Engineer, AI - Python Company: Telnyx Location: United States Job Posted Time: 2026-09-10 14:07:14 Target Skills & Keywords : API Design, ArgoCD, CI/CD, Docker, FastAPI, Flask, Kubernetes, LLM, Python, SQL, SaaS, Salesforce, Slack, Systems Design, Systems Engineering About the job Experience: •2+ years of software engineering experience building backend services in Python Required Skills: •You'll partner with Engineering Leads and Technical Product Managers to understand the problem space, then translate those problems into well-architected, observable, and maintainable software. This isn't prompt engineering and it isn't gluing together SaaS tools - it's systems engineering with AI as a core primitive. •This is a hands-on builder role with high ownership. You'll make architectural decisions, ship iteratively, debug production issues, and care deeply about what happens after code merges. •Design and build multi-agent AI systems in Python that handle complex, multi-step business workflows - qualification, email generation, routing, enrichment, and outbound orchestration •Architect model-agnostic abstraction layers that decouple business logic from LLM providers, enabling flexibility across Claude, GPT, and open-source models •Build and operate backend services (FastAPI/Flask) deployed on Kubernetes with CI/CD, managing the full lifecycle from deployment configuration to production reliability •Design tool-use patterns for AI agents - structured function calling, multi-step reasoning, state management across conversation turns, and graceful handling of model failures •Build integrations across external systems (CRM, enrichment APIs, outreach platforms, Slack) with proper error handling, retries, rate limiting, and data contracts •Instrument and monitor AI systems in production — build observability into agent behavior, track success rates, detect regressions, and debug non-deterministic failures Qualifications: •Production experience building multi-step AI agent systems — stateful workflows where models make decisions, call tools, and operate across multiple turns, not single-shot API wrappers •In-depth knowledge of LLM internals as they affect system design: context window management, token budgets, cost/latency/capability tradeoffs across models, structured outputs, and strategies for handling hallucination and refusals •Solid software architecture fundamentals: API design, state management, fault tolerance, and graceful degradation when upstream services fail •Production experience with containerized deployments (Docker, Kubernetes) and CI/CD pipelines •Proficiency with SQL and data systems for building targeting, enrichment, and analytics pipelines •Built observability into production systems — structured logging, tracing, alerting, and monitoring that you actually use to debug issues •High ownership: you deploy your own code, investigate your own incidents, and close the loop between what you shipped and how it performs •Background in growth engineering, marketing automation, or revenue operations tooling •Contributions to or experience with open-source AI agent frameworks •Operational familiarity with ArgoCD, StatefulSets, or Kubernetes operations beyond basic deployments Compensation: •Flexible work environment (work from home / hybrid options) Interested candidates, please apply directly through the job posting on company's career page or try via AI auto apply on this platform. Don't miss this opportunity to join a forward-thinking team!