AI Engineer (Member of Technical Staff)

Change the world working for a scrappy, data-driven, and customer-focused startup that's revolutionizing financial operations with AI-driven workflow automation. If you know how to architect state-of-the-art LLMs, optimise RAG architectures, and want to build intelligent AI agents that eliminate inefficiencies in financial modelling, this is going to be the position for you.

As an AI Engineer, you will build cutting-edge solutions at the intersection of automation and artificial intelligence ensuring scalability, performance, and user experience standards. You will focus on creating minimum loveable products that empower financial professionals to focus on strategic decision-making rather than tedious tasks. You'll design intelligent systems that exceed our customers' expectations and transform how finance professionals analyse data, gain insights, and make informed decisions—faster and smarter. We have full-time roles available with remote work flexibility, hybrid, or on-site based on your preferences and seniority.

Qualification

• BS or MS in Computer Science, Statistics, or Mathematics with proven experience in ML and AI.
• 2+ years of experience in ML/DL model training, deployment, and building data science pipelines.
• Proficiency in Python or GoLang, TensorFlow, PyTorch, and Scikit-Learn.
• Experience with LLM and AI frameworks such as Langchain, LlamaIndex, CrewAI, Hugging Face Transformers, and OpenAI API.
• Strong understanding of Retrieval-Augmented Generation (RAG) architectures, vector ,search, embeddings, reranking models, and LLM-based dialogue systems.
• Excellent communication skills to articulate technical concepts.
• You build great relationships with everyone you work with and collaborate effectively in a cross-functional agile environment.
• Hands-on experience with micro services, scalable systems, and client-server applications.
• Strong understanding of HTTP REST, gRPC, WebSockets, WebRTC, and async Python frameworks like FastAPI.
• Energy, excitement, and passion for what's coming next. You don't wait to be told what's coming, you go out and find it.
  
  

Bonus Points

• Deep understanding of LLM architectures and experience fine-tuning or instruction-tuning LLMs.
• Experience in evaluating LLMs and Agents to quantify their performance and ground results.
• Familiarity with prompt tuning methodologies and frameworks like self-prompting, DSPy, and Banks.
• Managed data acquisition, experimentation, and analytics to improve algorithmic performance, focusing on RAG and multi-stage AI workflows.
• Conducted testing in prompt engineering, RAG, and RLHF to enhance model/system efficacy.
• Experience with LLM function calling, information retrieval, and deploying LLM-driven RAG and Agent applications.
• Ability to design, execute, and analyze A/B experiments to measure workflow reliability.
  
  

Perks

• Competitive compensation
• Unlimited PTO
• AI Assistants for work (Coding, General Purpose, etc.)