VCI Technology

Senior/Lead AI Engineer (FastAPI + Advanced LLM Ops) We are building an intelligent, high-performance trading assistant platform used in forex, equities, futures, and options. Our stack combines FastAPI, SQLAlchemy, LangChain, ChromaDB, Redis, MySQL/MongoDB, AWS, and modern LLM APIs (ChatGPT, Claude, Sonar, etc.). Were looking for a Senior/Lead AI Engineer who can take this platform to the next level using state-of-the-art AI design patterns and agentic architectures—not just using APIs, but engineering living, evolving, self-improving AI systems. What You’ll Own Design and build agentic AI systems for trading intelligence Implement ACE (Agentic Context Engineering) loops to continuously improve AI performance without retraining Build MCP (Model Context Protocol)-style architectures for modular, tool-using agents Create self-healing, self-correcting prompts that reflect reason rewrite Apply K.E.R.N.E.L. prompt patterns to ensure stability, reproducibility, and versioning Integrate multiple LLM providers (OpenAI, Claude, Sonar, etc.) with dynamic routing Build AI-powered workflows: strategy generation, signal analysis, automated reporting, risk summaries, policy enforcement Architect scalable backend using FastAPI + AWS + Redis + SQLAlchemy Optimize inference latency and cost using caching, vector databases (ChromaDB), and smart context retrieval Work closely with trading and product teams to build domain-specific AI intelligence Why This Role Matters We believe the future of trading operations is AI-native. We are turning prompts into living playbooks, agents into co-pilots, and context into our competitive moat. Your innovations will directly improve: Trading decision accuracy Operational efficiency Cost and latency (up to ~87% reduction with ACE) Prompt stability (K.E.R.N.E.L. principles) Reasoning performance (+8–10% as reported in AI finance benchmarks) Our Tech Stack Backend & API: FastAPI, Python, SQLAlchemy, Alembic, Pydantic AI & NLP: OpenAI, Claude, LangChain, ChromaDB, Vector DB, ACE loops, K.E.R.N.E.L. patterns, MCP-style tool protocols Databases: MySQL, MongoDB, Redis Cloud/Infra: AWS Architecture: Modular services (api, controllers, core, crud, rag, services, prompts) Must-Have Experience 4+ years Python backend (FastAPI preferred) Strong LLM API experience (OpenAI, Claude, etc.) Built intelligent agent systems or tool-using architectures Experience with vector search / RAG / LangChain Strong prompt design with versioning & testing SQL and NoSQL database experience AWS-based backend deployments Can translate domain problems (trading/finance) into AI workflows Nice to Have / Big Plus Experience with ACE, MCP, K.E.R.N.E.L. Built self-improving prompt systems Designed multi-agent orchestration Knowledge of trading systems or quant workflows Hands-on with Redis caching and async performance optimization Deployed high-availability AI systems in production What We Offer Opportunity to build the AI brain of a trading platform Full ownership over AI architecture & innovation Work with cutting-edge LLM techniques before the market