Salary
≈ $26k – $71k per year (Estimated)
Location
In office (Bengaluru)
Seniority
Middle · 3+ years exp
Overview
Company
Impact
Profile match
Bluno is a fintech SaaS platform transforming international trade by streamlining B2B payments and compliance, enabling MSME exporters to navigate regulations and accelerate cross-border transactions confidently.
Responsibilities:
- Design, develop, and deliver end-to-end LLM-powered features, retrieval-augmented generation, agentic workflows, prompt engineering, and tool calling using LLM APIs (OpenAI, Anthropic, Gemini) and orchestration frameworks such as LangChain and LangGraph.
- Conduct in-depth analysis of the data and documentation that underpin global trade, identifying the patterns, structures, and edge cases that determine what AI systems can reliably deliver.
- Translate those findings into product capability, defining and scoping new AI features in collaboration with product and the founding team.
- Establish evaluation and monitoring for AI features: define quality metrics, build evaluation sets, diagnose failure modes, and drive improvements in accuracy, reliability, latency, and cost.
- Conduct applied research and structured experimentation across model behaviour, retrieval strategies, and prompting techniques, and assess emerging approaches for production suitability.
Requirements:
- Bachelor's degree in Computer Science, Engineering, or a related quantitative discipline.
- 3-4 years of experience building AI/ML systems, predominantly in applied AI or machine learning engineering.
- An Intelligent layer that global trade runs on.
- Demonstrated production experience with LLM APIs, retrieval-augmented generation, prompt engineering, tool calling, agentic workflows, and orchestration frameworks (LangChain, LangGraph, or equivalent).
- Experience establishing evaluation and monitoring for AI systems in production, including failure analysis and optimisation for accuracy, latency, and cost.
- Strong proficiency in Python, with the data skills to work effectively with large, unstructured, and imperfect datasets.
- Working knowledge of machine learning and applied statistics, sufficient to select appropriate methods and measure impact rigorously.
- Analytical rigour and intellectual curiosity, with the ability to investigate an unfamiliar domain and distinguish substantive techniques from prevailing hype.
- Excellent communication skills and a proven ability to work autonomously in a fast-paced startup environment.
- Skills: Python, LLM APIs (OpenAI, Anthropic, Gemini), Retrieval-Augmented Generation, Prompt Engineering, Agentic Workflows and Tool Calling, LangChain / LangGraph, AI Evaluation and Observability, SQL, Machine Learning, Applied Statistics.
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