
Senior/Lead AI Engineer
2 days ago
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
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