We are seeking a highly skilled Python API Developer with strong expertise in building scalable, secure APIs, along with AI/ML knowledge and finance domain experience.
The ideal candidate will design, develop, and optimize API-driven systems that integrate financial data platforms with AI-powered analytics and decisioning engines.
You will collaborate with AI engineers, data scientists, and finance SMEs to deliver
intelligent, high-performance solutions for trading, risk management, fraud detection,
regulatory compliance, and financial reporting.
Key Responsibilities
API Development
Design, build, and maintain RESTful & GraphQL APIs using Python (FastAPI,
Flask, Django REST).
Ensure scalability, low-latency, and secure API communication for financial
applications.
Implement authentication/authorization frameworks (OAuth2, JWT, SSO).
AI & Data Integration
Integrate APIs with AI/ML models (predictive risk models, fraud detection,
portfolio optimization).
Work with data pipelines (ETL/ELT) to consume structured/unstructured
financial data.
Enable real-time scoring/inference APIs for AI models.
Finance Domain Use Cases
Collaborate with finance SMEs to implement APIs for risk assessment,
compliance reporting, fraud detection, and predictive analytics.
Build API endpoints that interface with market data providers, trading
systems, and regulatory platforms.
DevOps & Security
Implement API monitoring, logging, and performance optimization.
Ensure compliance with financial data security standards (e.g., SOC2, PCI
DSS, GDPR).
Automate CI/CD workflows for API deployment in cloud environments (AWS,
Azure, GCP).
Collaboration
Partner with data scientists to operationalize AI/ML models.
Work closely with finance stakeholders to translate requirements into
technical solutions.
Mentor junior developers on best practices for Python API and AI integration.
Required Skills & Experience
Core Technical
Strong expertise in Python and modern API frameworks (FastAPI, Flask, Django
REST).
Experience with API lifecycle management, performance tuning, and versioning.
Knowledge of databases (Postgres, MySQL, MongoDB, Redis) and ORMs
(SQLAlchemy, Django ORM).
Familiarity with message brokers & streaming (Kafka, RabbitMQ).
AI/ML Knowledge
Understanding of ML model deployment (scikit-learn, TensorFlow, PyTorch).
Knowledge of AI integration patterns (batch inference, real-time APIs, vector
databases).
Exposure to NLP in finance (sentiment analysis, document intelligence, chatbots).
Git/GitHub, CI/CD pipelines, Agile/Scrum methodology.
Strong problem-solving and system design skills.
Experience with cloud environments (AWS, Azure, GCP) and containerization
(Docker, Kubernetes).
Finance Domain
Experience with financial datasets (trades, positions, risk, compliance, payments).
Understanding of capital markets, investment banking, or fintech systems.
Familiarity with risk models (VaR, credit risk, fraud detection) and regulatory
frameworks (Basel III, MiFID, AML/KYC).
Exposure to LLM-based APIs (OpenAI, Hugging Face, LangChain) for finance
applications.
Contributions to open-source projects or AI/FinTech communities.
Bachelors or Master's degree in Computer Science, Data Science, or Financial
Engineering.