Senior Engineer, AI

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YogiTrades

WebsiteLinkedInAll Job Openings

11 - 50 employees

₿ Crypto

💸 Finance

💳 Fintech

Crypto • Finance • Fintech

YogiTrades is a platform designed for Indian traders to engage in futures and options trading on cryptocurrencies like Bitcoin and Ethereum. The platform operates 24/7, allowing users to trade without owning any actual crypto, with all transactions settled in INR. Registered with the Financial Intelligence Unit of India, YogiTrades complies fully with local regulations, providing a secure and trustworthy trading environment. It offers innovative trading features, smart margining schemes, and deep analytics to enhance user experience. Users can make smaller initial investments and enjoy daily, weekly, and monthly expiries, ensuring flexibility and a wide range of opportunities. The platform is also integrated with efficient customer support and community interaction features.

📋 Description

• Design, build, and maintain production AI applications end-to-end: backend, frontend, and inference services. • Architect RAG systems using vector databases, embedding models, and chunking strategies optimised for accuracy and latency. • Build agentic workflows with tool/function calling, multi-step reasoning, and structured output parsing, with accuracy and control as priority. • Write and iterate on system prompts, few-shot examples, and prompt chains to maximise output quality. • Implement function calling, tool-use patterns, and structured JSON/XML output handling using frontier and lightweight models from providers like Anthropic and OpenAI. • Drive cost optimisation: model selection, caching, token budgeting, and request batching at scale. • Build and maintain evaluation frameworks to measure accuracy, relevance, hallucination rates, and regression across prompt and model changes. Experience with observability tools (Sentry, Opik, etc.) is a must. • Work with message queues (RabbitMQ), caching layers (Redis), and relational databases (PostgreSQL) powering AI service backends. • Deploy and manage AI services on Kubernetes with CI/CD pipelines on AWS/GCP. • Integrate AI capabilities with third-party platforms (Telegram bots, chat widgets, etc.). • Contribute to architectural decisions: model selection, hosting (cloud APIs vs. self-hosted), and build-vs-buy trade-offs.

🎯 Requirements

• 5+ years shipping production software systems. • 2 years building AI/LLM-powered applications end-to-end with real users and volume. Not prototypes. • Strong experience with RAG architectures: vector databases, embedding models, chunking/indexing strategies, and retrieval evaluation. • Deep understanding of LLM capabilities and limitations: prompt engineering, function/tool calling, structured outputs, context window management, and multi-turn conversations. • Experience with LLM provider APIs and abstraction layers (OpenAI, Anthropic, LiteLLM, OpenRouter, or similar). • Proficiency in Python (Flask/FastAPI) and/or Node.js/TypeScript (Next.js, Vercel AI SDK). Golang experience is a plus. • Hands-on experience building evals, tracking quality metrics, and debugging non-deterministic outputs in production. • Familiarity with cost optimisation: model routing, caching, token usage monitoring, and prompt compression. • Solid fundamentals in data structures, algorithms, and system design. • Experience with containerised deployments (Docker, Kubernetes) and cloud platforms (AWS/GCP). Practical understanding of k8s concepts and trade-offs is a must.