Job Description

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.

The Role

Most FP&A roles ask you to run a process someone else designed. This one asks you to build the process and then run it.

We're replacing our Anaplan-style planning stack with something faster, more automated, and built around AI agents, APIs, and connected systems instead of manual spreadsheet chains. You'll be the finance half of that build, working closely with our FP&A Engineer to design the tooling from scratch. Once it's live, you'll own the forecasting, modeling, and strategic decision support that runs on top of it.

This is not a traditional FP&A role with some added automation. It's for someone who genuinely wants to understand how a finance function works, rebuild the parts that can be better, and then use what they built to answer the business's hardest questions.

Here's the part that actually matters most: agentic AI isn't a side initiative at Telnyx, it's how we work. Every employee builds daily with AI agent frameworks and tools, running on company-issued hardware, connected into leading model providers to build and run agents as part of normal day-to-day work. This isn't a "nice to have exposure to AI" line item. You should already be someone who builds agents for fun or for work, or be genuinely itching for a job where that's expected of you rather than tolerated. If that doesn't excite you, this specific role will feel like a mismatch no matter how strong your modeling is.

Responsibilities

Phase 1: Build

• Partner directly with our FP&A Engineer to design and ship our next-generation planning, forecasting, and reporting infrastructure.
• Build and extend agents on our own stack, including our internal agent frameworks, control plane, and agent-to-agent tooling to eliminate manual FP&A workflows. Not just document them, replace them.
• Help shape the architecture, including what gets automated, what requires human judgment, and where the models need guardrails.

Phase 2: Own

• Build driver-based models across revenue, gross profit, headcount, operating expenses, and cash.
• Lead scenario planning, sensitivity analysis, and ROI work for investments, pricing, hiring, and commercial decisions.
• Own and continuously improve forecasting, budgeting, and long-range planning.
• Turn messy, incomplete, or contradictory data into a clear point of view on what's actually driving the numbers.
• Translate complex analysis into executive-ready answers to four questions: What changed? Why? What does it mean? What should we do next?

Every Day, Regardless of Phase

• Get pulled into urgent modeling questions with little warning. It could be a hiring decision, a revenue swing nobody can explain yet, or a commercial deal that needs a fast financial assessment. Your job is to turn it into structured analysis leadership can act on quickly.
• Partner with Accounting, BI, and other business leaders so models reflect how the business actually operates, not just how the spreadsheet says it should.

Who This Role Is For

You'll love this if you get energy from a blank page and figuring out how data and systems actually connect, then automating the parts that shouldn't be manual anymore.

You want to be close to the decisions, not three steps removed from them. When someone throws you a question you've genuinely never seen before, your instinct is "let me figure this out," not "let me find the template." And building your own agents to handle the repetitive parts of the job feels like a natural way to work, not an extra task.

You'll probably be frustrated here if you want a fixed, unchanging process to administer rather than one you're expected to keep improving, if "ambiguous" and "urgent" aren't words you want describing your Tuesday, or if AI tooling is something you'd rather leave to engineering.

What We Are Looking For

• Real, hands-on experience building or working with AI agents. This is a requirement for this role, not a nice-to-have. Comfort with leading model providers and agent frameworks, or a demonstrated track record of picking up new tools in this space fast.
• A builder's instinct: you're comfortable learning how systems and data fit together and reaching for technology to solve finance problems, not just Excel.
• Working knowledge of automation, APIs, SQL, Python, or similar. You don't need to be an engineer, but you need to be conversant enough to partner with one as an equal.
• FP&A, strategic finance, corporate finance, or similar experience with genuinely strong financial modeling skills.
• Genuine comfort building an analysis from a loosely defined, half-formed business question. You don't wait for someone to hand you a clean brief.
• Sharp judgment about where precision adds real value versus where speed matters more.
• Strong, confident communication. You can walk senior leadership through a complex model without losing them.
• A solid understanding of financial statements and how operational decisions flow through to financial results.

Why Now

You're not joining an established process and learning its quirks. You're one of only a few people designing what the process even is, using a technology stack that's already embedded in how the broader company works. The agents and systems you stand up in your first several months become the infrastructure the finance org runs on afterward, and you'll have direct input into both the tooling and the business decisions it powers.

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