Note: The job is a remote job and is open to candidates in USA. All IT Solutions is seeking a highly skilled AI & Financial Engineering Developer who combines deep expertise in artificial intelligence/machine learning with quantitative finance. This remote role focuses on designing and deploying AI-powered applications and quantitative models for financial use cases, while collaborating with cross-functional teams.
Responsibilities
- Design, develop, and deploy machine learning models and AI-powered applications for financial use cases
- Build and optimize deep learning, NLP, and generative AI solutions
- Develop data pipelines and feature engineering frameworks for model training and inference
- Implement MLOps best practices including model versioning, monitoring, and continuous deployment
- Stay current with state-of-the-art AI research and evaluate applicability to financial domains
- Develop quantitative models for pricing, risk management, and portfolio optimization
- Implement algorithmic trading strategies and backtesting frameworks
- Build financial simulation engines (Monte Carlo, stochastic modeling, etc.)
- Design and develop derivatives pricing models and fixed-income analytics
- Create real-time market data processing and analytics systems
- Write production-quality, scalable, and maintainable code
- Architect and build high-performance distributed systems
- Develop RESTful APIs and microservices for financial applications
- Implement robust testing, CI/CD pipelines, and documentation practices
- Collaborate with cross-functional teams including traders, quants, risk managers, and data engineers
Skills
- Education: Master's or PhD in Computer Science, Financial Engineering, Quantitative Finance, Mathematics, Physics, or a related quantitative field
- Experience: 7+ years of professional software development experience, with at least 3 years in AI/ML and 2+ years in financial services or fintech
- Programming Languages: Expert proficiency in Python; strong skills in C++, Java, or Scala
- AI/ML Expertise: Hands-on experience with TensorFlow, PyTorch, scikit-learn, and large language models (LLMs)
- Financial Knowledge: Strong understanding of financial instruments (equities, fixed income, derivatives, structured products), market microstructure, and quantitative risk measures (VaR, Greeks, CVA)
- Mathematics: Advanced knowledge of stochastic calculus, linear algebra, probability theory, and numerical methods
- Data & Infrastructure: Experience with SQL/NoSQL databases, cloud platforms (AWS, Azure, or GCP), and big data technologies (Spark, Kafka)
- CFA, FRM, or equivalent financial certification
- Experience with reinforcement learning applied to trading or portfolio management
- Knowledge of blockchain/DeFi protocols and smart contract development
- Familiarity with regulatory frameworks (Basel III/IV, MiFID II, Dodd-Frank)
- Publications in AI/ML or quantitative finance journals
- Experience with real-time streaming systems and low-latency architectures
- Proficiency with LLM fine-tuning, RAG architectures, and AI agents for financial applications
Company Overview