Forward Deployed Engineer – Peakflo

Peakflo is a rapidly growing Agentic AI company focused on transforming how global finance teams operate through intelligent automation. By building advanced AI-driven workflows, Peakflo helps organizations streamline financial operations, reduce manual effort, and improve efficiency across core finance processes.

The company is backed by leading global investors and accelerators and is a proud alumnus of the Y Combinator (W22) and the Google AI Accelerator. Peakflo has been featured by major technology and finance publications including TechCrunch, PYMNTS, and Grit Daily for its innovation in AI-powered financial automation.

With a globally distributed team and a culture focused on ownership, curiosity, and innovation, Peakflo provides an environment where engineers can work on challenging problems while building impactful AI products for finance teams around the world.

Role Overview

Peakflo is seeking a motivated Forward Deployed Engineer (FDE) who will bridge the gap between advanced AI technologies and real-world financial workflows. In this role, you will work closely with engineering, product, and operations teams to develop, deploy, and optimize AI-powered solutions that improve financial operations for customers.

You will contribute to building agentic machine learning systems, designing prompt-based AI workflows, integrating large language models, and automating data processes. The role combines expertise in machine learning, backend development, and business workflow optimization.

Key Responsibilities

Voice AI and Prompt Engineering

Design conversational prompt flows optimized for voice-based interactions and natural speech patterns.
Develop prompts suitable for text-to-speech systems to ensure clarity and avoid ambiguity.
Continuously refine prompts using LLM feedback loops to detect hallucinations and improve response quality.
Implement A/B testing frameworks, prompt versioning, and performance evaluation pipelines.
Collaborate with engineering teams to integrate prompts with speech recognition systems, intent extraction pipelines, and telephony APIs.
Ensure voice-based AI systems maintain real-time responsiveness and low latency.

Agentic AI Architecture, LLMs and RAG

Develop hierarchical AI workflows consisting of multiple specialized agents such as research agents, finance agents, and editing agents.
Optimize the performance of large language models including Gemini, GPT, and Claude.
Integrate retrieval-augmented generation (RAG) with enterprise knowledge bases and financial APIs.
Design systems that minimize hallucinations while maintaining strong contextual accuracy.
Architect integrations between LLM systems, email interactions, chat interfaces, and third-party tools.
Develop complementary AI components such as OCR models for document processing.

Data Analytics and Workflow Automation

Analyze financial workflows and business processes to identify operational bottlenecks and improvement opportunities.
Automate reporting, data processing, and operational workflows using Python and SQL.
Develop dashboards and monitoring frameworks to track system performance and data quality.
Collaborate with product and engineering teams to translate business requirements into technical solutions.
Maintain clear documentation of workflow logic, automation scripts, and system architectures.

Required Qualifications

Bachelor’s or Master’s degree in Computer Science, Machine Learning, Data Science, Statistics, or a related technical field.
0.5 to 2 years of industry experience working with Machine Learning, Natural Language Processing (NLP), or Large Language Models.
Strong proficiency in Python programming with a focus on backend development.
Experience working with or deploying machine learning models in production environments.
Familiarity with cloud platforms such as Google Cloud.
Strong written and verbal communication skills in English.

Preferred Skills

Experience with LLM orchestration frameworks such as LangChain or LlamaIndex.
Knowledge of advanced NLP techniques and related libraries.
Understanding of software engineering best practices and version control systems such as Git.
Strong interest in AI technologies and their applications in business automation.

Benefits

Competitive compensation package.
Comprehensive employee benefits.
Opportunities for rapid career growth and skill development.
Collaborative and innovative work environment.
Flexible working hours and remote work options.

Interview Process

Initial Screening and Technical Discussion: A conversation focused on your background, experience, and foundational technical knowledge. Candidates may be asked to submit a transcript from an AI coding agent session demonstrating practical AI development skills.
Hands-On Technical Interview: A practical session involving real-world engineering problems that evaluate problem-solving abilities and coding skills.
Final Technical Interview: A deeper discussion with the CTO and Co-Founder focusing on architectural thinking, complex problem solving, and cultural fit.
Reference Checks: Professional references will be contacted to understand your work experience and collaboration style.

About Peakflo

Peakflo provides a unified platform that simplifies financial operations through automation and intelligent workflows. With simple APIs and one-click ERP integrations, the platform enables businesses to streamline invoice-to-cash and procure-to-pay processes.

More than 100 companies ranging from high-growth startups to large enterprises use Peakflo to automate finance operations, reduce manual workload, and accelerate payment cycles.

Save up to 2000 man-hours per month on finance operations.
Receive customer payments 15–25 days faster.
Reduce vendor payment processing time by up to 50%.
Automate complex processes such as three-way invoice matching.