AI Engineer

Summary

Domyn is a company specializing in the research and development of Responsible AI for regulated industries, including financial services. They are hiring an AI Engineer to help build AI solutions for financial workflows, focusing on the engineering and deployment of scalable AI systems.

Responsibilities

• Build and maintain Agentic AI Systems capable of delivering complex tasks such as navigating enterprise-scale inventories of structured and unstructured information sources, optimizing portfolio construction and evolving trading strategies in the financial industry
• Develop APIs and integration points for AI services within our product ecosystem
• Ensure AI models are secure, auditable, and compliant with industry standards
• Optimize AI models and agentic pipelines for performance, latency, and resource utilization
• Implement systems for model evaluation, monitoring, and continuous improvement
• Troubleshoot complex issues in AI systems and implement solutions
• Stay current with emerging techniques in AI engineering and LLM deployment
• Collaborate with researchers and financial SMEs to translate prototypes and business requirements into technical solutions fully integrated with the rest of the platform

Skills

• Bachelor's or Master's degree in Computer Science, Engineering, or related technical field
• 3+ years of experience in Software/ML/AI engineering, with a proven track record of delivering scalable AI solutions ideally on financial systems
• Strong Python programming skills and experience with data science libraries, e.g., NumPy, Pandas, Scikit-learn, writing efficient production-level code, which is well-written and explainable
• Experience with deploying and scaling AI models in production environments
• Familiarity with large language models, transformer architectures, and generative AI
• Knowledge of cloud platforms (AWS, GCP, Azure) and containerization technologies
• Understanding of software engineering best practices (git, version control, CI/CD, testing)
• Experience with ML engineering tools and platforms (MLflow, Kubeflow, etc.)
• Strong problem-solving skills and attention to detail
• Ability to collaborate effectively in cross-functional teams
• Experience in the Financial Services industry (FinTech, Investment Banks, Fund Managers, etc.)
• Knowledge of distributed computing, large-scale model training, agentic framework design
• Experience with real-time inference systems and low-latency AI services
• Active contributor to open-source concepts or AI frameworks
• Knowledge of vector and graph databases and knowledge graphs

Qualifications

Must Haves

• Bachelor's or Master's degree in Computer Science, Engineering, or related technical field
• 3+ years of experience in Software/ML/AI engineering, with a proven track record of delivering scalable AI solutions ideally on financial systems
• Strong Python programming skills and experience with data science libraries, e.g., NumPy, Pandas, Scikit-learn, writing efficient production-level code, which is well-written and explainable
• Experience with deploying and scaling AI models in production environments
• Familiarity with large language models, transformer architectures, and generative AI
• Knowledge of cloud platforms (AWS, GCP, Azure) and containerization technologies
• Understanding of software engineering best practices (git, version control, CI/CD, testing)
• Experience with ML engineering tools and platforms (MLflow, Kubeflow, etc.)
• Strong problem-solving skills and attention to detail
• Ability to collaborate effectively in cross-functional teams

Nice to Haves

• Experience in the Financial Services industry (FinTech, Investment Banks, Fund Managers, etc.)
• Knowledge of distributed computing, large-scale model training, agentic framework design
• Experience with real-time inference systems and low-latency AI services
• Active contributor to open-source concepts or AI frameworks
• Knowledge of vector and graph databases and knowledge graphs

Benefits

• Performance-based bonuses
• Comprehensive benefits as part of the total compensation package