AI-Driven Financial Systems Engineer

Job Summary
We are seeking a highly skilled AI & Financial Engineering Developer who combines expertise in artificial intelligence, machine learning, and financial engineering to develop innovative solutions for financial use cases. This role involves designing AI-powered applications, developing quantitative financial models, building scalable software solutions, and collaborating with cross-functional teams to deliver high-performance financial systems.

Key Responsibilities

• Design, develop, and deploy machine learning models and AI-powered applications for financial use cases.

• Build and optimize deep learning, natural language processing (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.

• Evaluate emerging AI technologies and assess their 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, including Monte Carlo and stochastic modeling solutions.

• 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 develop high-performance distributed systems.

• Develop RESTful APIs and microservices for financial applications.

• Implement robust testing, CI/CD pipelines, and technical documentation.

• Collaborate with traders, quantitative analysts, risk managers, data engineers, and cross-functional teams to deliver technical solutions.

Required Qualifications

• 7+ years of professional software development experience.

• Experience developing APIs and AI-powered applications.

• 1–3 years of experience in the financial services or fintech industry.

• Strong programming experience with Python.

• Strong programming experience with C++ and/or Scala.

• Hands-on experience with AI/ML frameworks such as Tensor Flow, PyTorch, and scikit-learn.

• Experience working with large language models (LLMs).

• Strong understanding of financial instruments, including equities, fixed income, derivatives, and structured products.

• Knowledge of quantitative risk measures and financial modeling concepts.

• Strong mathematical foundation, including probability, linear algebra, numerical methods, and stochastic modeling.

• Experience with SQL/No

SQL databases.

• Experience with cloud platforms such as AWS, Azure, or Google Cloud Platform (GCP).

• Experience with big data technologies such as Spark and Kafka.

• Strong software engineering skills, including distributed systems, RESTful APIs, and microservices.

Preferred Qualifications

• Master's or PhD in Computer Science, Financial Engineering, Quantitative Finance, Mathematics, Physics, or a related quantitative field.

• Prior experience with Fannie Mae or Freddie Mac.

• Experience with agentic AI development.

• Experience with reinforcement learning for trading or portfolio management.

• Knowledge of blockchain, DeFi protocols, and smart contract development.

• Familiarity with financial regulatory frameworks such as Basel III/IV, MiFID II, or Dodd-Frank.

• Publications related to AI/ML or quantitative finance.

• Experience with real-time streaming systems and low-latency architectures.

• Experience with LLM fine-tuning, Retrieval-Augmented Generation (RAG) architectures, and AI agents for financial applications.

• Experience with Docker, Kubernetes, Terraform, Airflow, PostgreSQL, MongoDB, Redis, Git, CI/CD, MLflow, and Weights & Biases.

Certifications

• CFA, FRM, or equivalent financial certification preferred.