Forward Deployed Engineer (FDE) - (India/Remote)

🚀 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 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 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.

Here is what our interview process looks like for the Forward Deployed Engineer role. We value transparency and want to give you every opportunity to showcase your strengths, especially your fluency with modern AI development tools.

1. Initial Screening & Technical Theory This first round is a conversation to understand your background, experiences, and foundational technical knowledge. Special Note : If you advance to this round, we will ask you to reply to us with a transcript of a coding agent session you are particularly proud of. We are running this experimental step to give candidates a chance to show off their practical skills with AI coding tools. Many coding agents (e.g., Claude Code, Cursor) have an /export command or include a button allowing you to export a transcript. You can provide this to us in plain text or Markdown.

2. Hands-On Technical Interview A practical, hands-on session where you will work through real-world engineering problems similar to what you would face as an FDE. We focus on your problem-solving approach, coding proficiency, and how you translate requirements into working solutions.

3. Final Technical Interview with CTO & Co-Founder In this final technical round, you will meet directly with our CTO and Co-Founder. This is a deeper hands-on session focusing on architectural thinking, complex problem-solving, and assessing how well you align with our high-performance engineering culture.

4. Reference Checks As the final step before extending an offer, we will ask you to provide professional references. We will have a brief chat with them to learn more about your past work dynamics, your strengths, and how we can best support your success on the team.