Scan your resume against ATS criteria for this Applied AI Engineer role at Prodigal.
Prodigal is the connected AI platform leading financial institutions use to run their operations.
We work with banks, lenders, credit unions, and other financial companies that lend money to people and manage those relationships over time.
These institutions make millions of high-stakes decisions every day. Who should they reach? When should they reach them? What should they say or offer? When should a case move to a human? How should that change based on the borrower, the account, previous interactions, and the regulations involved?
Getting those decisions right requires a deep understanding of the people, processes, rules, and edge cases behind them.
Prodigal has spent the last eight years building that understanding. More than a billion interactions between financial institutions and their customers have shaped the intelligence, guardrails, and AI agents we now run in production across North America.
Today, our AI agents analyze conversations, capture context, guide human agents, decide the next action, conduct customer conversations, orchestrate outreach, and help people complete payments and resolutions. They are connected, so what is learned in interaction can inform what happens next.
We are expanding this swarm of AI agents across more of the work financial institutions do: originations, document processing, back-office workflows, servicing, and other critical operations where money, identity, people, and regulation intersect.
We are backed by Y Combinator, Accel, and Menlo Ventures, and work with 100+ financial institutions across North America. Listen directly from our CTO, Cofounder - Sangram Raje
We're looking for an AI Engineer to join the proAgent team and work on the systems that power our autonomous voice agents in live financial conversations. You'll work alongside a small, high-agency team where you will have real ownership over features and components from day.
This is a hands-on engineering role. You'll be deep in the code - building agent logic, integrating speech models, tuning prompts, and debugging gnarly real-time issues. You don't need to have done all of this before, but you need to be the kind of engineer who figures things out fast, takes feedback well, and ships.
Build and maintain components of the agentic runtime that powers multi-turn financial conversations - covering payment negotiations, compliance guardrails, and objection handling
Implement context management logic that tracks consumer state, conversation history, and business rules across long, branching dialogues
Write and iterate on primitives that balance conversational fluidity with structured reasoning - the agent needs to feel human while making verifiable decisions
Work on our real-time voice pipeline with a target of sub-1s latency across transcription, reasoning, and synthesis
Contribute to VAD tuning and turn-taking logic that makes conversations feel natural
Help evaluate and integrate speech models (STT, TTS, speech-to-speech) - we currently work with ElevenLabs and Cartesia for TTS, and Deepgram for STT, and are always exploring what's next
Debug streaming audio and WebRTC issues in production
Write and refine prompts, implement orchestration flows, and contribute to model routing logic
Build components of our evaluation framework - helping measure agent quality across conversation quality, empathy, and compliance adherence
Stay curious about new models and tools - flag opportunities and contribute to build-vs-integrate discussions
2 – 5 years of hands-on engineering experience, with good exposure to building or working with ML or AI systems in production.
Solid Python fundamentals - you are comfortable writing clean, maintainable code and debugging production issues.
Some experience working with LLMs: prompt engineering, API integrations, or building simple pipelines or agents.
High bias for action - you don't wait to be told exactly what to do, and you push yourself to ship rather than over-engineer.
Strong fundamentals in Python; familiarity with TypeScript is a plus.
Eager to learn in a fast-moving environment, take ownership of your work, and ask good questions.
Exposure to voice AI: speech recognition, synthesis, or telephony systems - even if through personal projects or coursework
Any background or interest in fintech, lending, or collections
You've tinkered with Twilio, LiveKit, ElevenLabs, or similar real-time infrastructure
You've built a small agentic system - even a side project - that combines LLM reasoning with structured actions
Familiarity with streaming protocols, WebRTC, or low-latency system design
From day 1, Prodigal has been defined by talented, humble, and hungry leaders and we want this mindset and culture to continue to blossom from top to bottom in the company. If you have an entrepreneurial spirit and want to work in a fast-paced, intellectually-stimulating environment where you will be pushed to grow, then please reach out because we are looking to build a transformational company that reinvents of the biggest industries in the US.
To learn more about us - please visit the following:
Our Story - https://www.prodigaltech.com/our-story
What shapes our thinking - https://link.prodigaltech.com/our-thesis
Our website - https://www.prodigaltech.com/
How to apply for Applied AI Engineer at Prodigal?
Click the "Apply on Company Website" button on this page to submit your application directly on the employer's official portal.
What is the salary for this role?
Salary details will be discussed during the interview.
What experience is required?
5+ yrs of experience is required.
Is this position still open?
Yes, currently active and accepting applications.
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