Software Engineer, GTM AI - Python

We're looking for a Software Engineer who builds and operates the AI-native backend systems powering our go-to-market motion. You'll design multi-agent architectures, build reliable integrations across complex business systems, and own services end-to-end from prototype through production.

The systems you build orchestrate LLM-powered agents that handle real business workflows - qualifying leads, generating emails, routing meetings, enriching contacts, and managing outbound campaigns. These are stateful, multi-step agent systems running on Kubernetes that make decisions, call tools, and interact with external APIs under real constraints: rate limits, token budgets, cost targets, and data quality issues.

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
• Design and run experiments (A/B tests, prompt variations, model comparisons) with proper evaluation infrastructure to measure what's actually working, Remote or Hybrid 70K-87K Annually Entry level 70K-87K Annually Entry level Big Data * Food * Hardware * Machine Learning * Retail * Automation * Manufacturing Support continuous improvement by training teams on CI tools and DMS, collecting and validating data, facilitating root-cause analysis, establishing work standards, and qualifying colleagues. Drive KPI scorecards, use Excel and analytics tools, apply lean/TPM methods, and manage related projects in a manufacturing environment. Top Skills: Daily Management System (Dms)Data Analytics ToolsExcelIl6S (Lean Six Sigma)LeanTpm Airwallex

Talent Acquisition Partner, Business and GTM

9 Hours Ago Remote or Hybrid Senior level Senior level Artificial Intelligence * Fintech * Payments * Business Intelligence * Financial Services * Generative AI Full-cycle recruiter owning hiring for Business and GTM functions (Sales, Legal, Risk, Compliance, Finance, Operations, Strategy, Marketing). Partner with senior leaders to design sourcing strategies, assess candidates, manage offers and negotiations, track recruiting metrics, and improve workflows. Champion employer brand and deliver diverse, high-caliber talent in a fast-paced, hybrid Toronto environment. Top Skills: Ashby PwC

• 2+ years of software engineering experience building backend services in Python
• 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
• Strong understanding 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
• Experience testing and evaluating non-deterministic AI systems - you understand that assert output == expected doesn't work and have built or used alternatives
• 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
• Experience integrating with external APIs at scale - auth flows, rate limiting, retries, data normalization, and managing the operational complexity of multiple third-party dependencies
• 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

Nice to Have

• Experience with specific GTM/RevOps systems (Salesforce, Apollo, Lusha, enrichment providers) or similar complex business platforms
• Background in growth engineering, marketing automation, or revenue operations tooling
• Experience with Slack bot development or conversational AI interfaces
• Contributions to or experience with open-source AI agent frameworks
• Familiarity with ArgoCD, StatefulSets, or Kubernetes operations beyond basic deployments

Build and operate AI-native backend services that orchestrate multi-step, stateful LLM agents for GTM workflows. Design model-agnostic abstractions, integrate external systems, deploy containerized services on Kubernetes, ensure observability, and run experiments to measure effectiveness. The summary above was generated by AI, Remote or Hybrid Denver, CO, USA 77K-202K Annually Senior level 77K-202K Annually Senior level Artificial Intelligence * Professional Services * Business Intelligence * Consulting * Cybersecurity * Generative AI Design and implement Epic payer platform IT solutions, perform complex data analysis and data mining/modeling, manage IT infrastructure alignment, mentor junior staff, and build client relationships to support operations transformation. Top Skills: ChroniclesData CourierEpic EcsaEpic OdbaEpic Payer Platform

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

About Telnyx Telnyx is an industry leader that's not just imagining the future of global connectivity-we're building it. From architecting and amplifying the reach of a private, global, multi-cloud IP network, to bringing hyperlocal edge technology right to your fingertips through intuitive APIs, we're shaping a new era of seamless interconnection between people, devices, and applications. We're driven by a desire to transform and modernize what's antiquated, automate the manual, and solve real-world problems through innovative connectivity solutions. As a testament to our success, we're proud to stand as a financially stable and profitable company. Our robust profitability allows us not only to invest in pioneering technologies but also to foster an environment of continuous learning and growth for our team. Our collective vision is a world where borderless connectivity fuels limitless innovation. By joining us, you can be part of laying the foundations for this interconnected future. We're currently seeking passionate individuals who are excited about the opportunity to contribute to an industry-shaping company while growing their own skills and careers. About the Team The RevOps team owns the systems layer, operations & automation that supports Telnyx's growth engine. Historically, that meant administering GTM tools used by humans: Salesforce, marketing automation, enrichment vendors, routing, campaign workflows, reporting, and vendor integrations. That operating model is changing. Telnyx is increasingly building AI agents and automation that interact directly with the GTM stack. The systems team now needs to support both human-facing workflows and bot-facing infrastructure: clean data, reliable integrations, durable automations, documented process, and scalable operating patterns.