AI-Driven Financial Systems Engineer

Compunnel Inc.; McLean (VA); Presencial; USD 160 000 - 220 000; Tempo integral

Resumo da oferta

Compunnel, Inc. seeks an AI & Financial Engineering Developer to design AI-powered financial applications, develop quantitative models, and build scalable software systems.

You will collaborate with traders, quant analysts, risk managers, and data engineers to deliver high-performance financial solutions. The role requires 7+ years in software development, expertise in Python, C++, and ML frameworks, plus hands-on experience with LLMs and financial instruments.

Qualificações

• ,
• 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 TensorFlow, 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/NoSQL 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.

Responsabilidades

• 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.
• 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.

Conhecimentos

Python

C++

Scala

ML frameworks

LLMs

Distributed systems

REST APIs

MLOps

Cloud platforms

Quantitative finance

Formação académica

Master's or PhD in CS/Financial Engineering

Quantitative Finance background

Ferramentas

Docker

Kubernetes

Terraform

Airflow

PostgreSQL

MongoDB

Redis

Git

CI/CD

MLflow

Weights & Biases

Descrição da oferta de emprego

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 TensorFlow, 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/NoSQL 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.