Peakflo is a rapidly growing Agentic AI company. We are revolutionizing the way global finance teams work with our cutting-edge agentic workflows, and we are actively seeking exceptional professionals across diverse disciplines to champion this transformation, uniting multidisciplinary expertise to propel our global strategic vision.
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 doVoice 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.
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.
Experience with multiple LLM platforms and orchestration frameworks (e.g., LangChain, LlamaIndex).
Familiarity with advanced Natural Language Processing (NLP) techniques and libraries.
Strong knowledge of software engineering best practices and version control systems (Git).
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.
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