Senior/Lead AI Engineer (FastAPI + Advanced LLM Ops)

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