Peakflo with its simple API and one-click ERP integrations, allows businesses to streamline their invoice-to-cash and procure-to-pay processes. 100+ companies, from scale-ups to enterprises, use Peakflo each to:

• Save 2000 man-hours/month on finance ops
• Get paid faster on customer invoices by 15-25 days
• Cut vendor bill payment time by 50%
• Automate three-way matching

🚀 Who we are & What we’re building

Peakflo is a rapidly growing Agentic AI company. We are revolutionizing the way global finance teams work with our agentic workflows, and we're looking for top talent from your institution to join our mission.

• Our Growth Story : Peakflo is backed by top-tier global accelerators and investors. We are proud alumni of the prestigious Y-Combinator (W22) and the Google AI Accelerator. Our momentum and impact have been recognized globally by top tech and finance publications:
  • TechCrunch Exclusive: Peakflo’s bid to build business payments for Southeast Asia attracts capital, customers
  • PYMNTS: Peakflo Raises $4.1M in Seed Funding to streamline vendor payments
  • Grit Daily: Latest Feature on Peakflo's Innovations

Our Culture : We believe in building a vibrant, high-performance culture that rewards curiosity, ownership, and innovation. Our team spans the globe, and we love coming together to solve hard problems and celebrate our wins. Most importantly, we have begun building an environment that provides the support and mentorship needed to succeed, learn, and grow. ❤️

💻 What we’re Looking For:

We are seeking a highly motivated and detail-oriented Forward Deployed Engineer (FDE) to join our dynamic team. In this role, you will bridge the gap between our core AI technology and real-world financial workflows. You will play a crucial part in developing, tuning, and implementing agentic machine learning solutions to drive business growth and optimize our products.

💪 What you’ll do

• Voice AI & Prompt Engineering
  • Craft Voice‑Optimized Prompt Flows: Design conversational flows that account for natural speech patterns (pauses, interruptions, intonation) optimized for voice-only interactions. Ensure prompts are clear for TTS pronunciation to avoid ambiguity.
  • Continuous Refinement: Use LLM feedback loops and "self‑reflection" to score outputs, detect hallucinations, and improve prompts. Set up pipelines for A/B testing, prompt versioning, and performance QA tailored to financial use cases.
  • Voice Integration: Collaborate with engineering teams to integrate prompts with speech recognition, intent extraction, LiveKit voice infrastructure, and telephony APIs. Ensure orchestration maintains real‑time responsiveness and low latency.
• Agentic Architecture, LLMs & RAG
  • Build Hierarchical Workflows: Develop finance AI agents that coordinate sub‑agents (e.g., a Research Agent, a Finance Agent, and an Editor Agent) for scalability and modularity.
  • Model Optimization: Apply expertise in leading LLMs (Gemini, GPT series, Claude) to optimize our AI Finance Employee performance. Ensure low latency and high efficiency across all applications.
  • Grounding & RAG: Integrate retrieval-augmented generation (RAG) with enterprise knowledge bases and financial APIs to prevent hallucinations and maintain tight context control around business domains.
  • System Integration: Architect and integrate LLM systems with third-party tools, email interactions, and user chat interfaces. Develop complementary components like customizable OCR models.
• Data Analytics & Workflow Automation
  • Process Improvement: Analyze business processes, data quality, and operational bottlenecks to identify improvement opportunities and present actionable recommendations.
  • Automation & Reporting: Automate workflows, data transformations, and reporting using Python and SQL. Build and maintain dashboards and data monitoring frameworks.
  • Collaboration & Documentation: Work closely with product, engineering, and operational teams to define requirements. Document workflow logic, scripts, and solution designs clearly.

🕵️‍♀️ Who we’re looking for

• Education: Bachelor's or Master's degree in Statistics, Machine Learning, Data Science, Computer Science, or a related technical field.
• Experience: 0.5 – 2 years of industry experience with Machine Learning, NLP, LLM fine-tuning, and prompt engineering.
• Excellent written and verbal communication skills in English.
• Technical Skills: Strong proficiency in Python programming (specifically back-end development).
  • Familiarity with cloud platforms (e.g., Google Cloud).
  • Hands-on experience deploying or working with ML models in production environments.
• Soft Skills: Excellent written and verbal communication skills in English; passionate about AI and its potential to transform business.

➕ We’re Particularly Interested In People Who Have:

1. Experience with multiple LLM platforms and orchestration frameworks (e.g., LangChain, LlamaIndex).
2. Familiarity with advanced Natural Language Processing (NLP) techniques and libraries.
3. Strong knowledge of software engineering best practices and version control systems (Git).

🙂Benefits :

• Competitive compensation package
• Benefits package
• Opportunity for rapid career growth and skill development.
• Collaborative and innovative work environment.
• Flexible work hours and remote work options.

We are looking for quick-thinking, problem-solving full stack engineers to build the next generation of fintech products. Our SaaS product is built using typescript, node.js and react.

You should apply if you are interested in backend, microservice distributed architecture; if you are looking to join a high-growth high-pace startup with great engineering culture; if you want to work in a passionate high-skilled team.