Senior AI Engineer

Key Responsibilities

• Lead building and maintenance of 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.
• Own development of 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.

Requirements

• Bachelor’s or Master’s degree in Computer Science, Engineering, or related technical field.
• 7+ years of experience in Software/ML/AI engineering, with a proven track record of delivering scalable AI solutions ideally on financial systems.
• Superb 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.
• Proven track record of deploying and scaling AI models in production environments.
• In-depth experience with large language models, transformer architectures, and generative AI.
• Good knowledge in at least one of the following applied machine learning fields: Recommender Systems, NLP, Information Retrieval, Causal Inference, Time Series, Knowledge Graph.
• Experience in infrastructure development for distributed systems and AI applications, proficient in cloud infrastructure, including AWS, Google Cloud, Azure.
• Well-versed in various data storage and warehouse solutions, such as Snowflake, Databricks, MongoDB, Oracle, SQL, and NoSQL databases.
• Strong understanding of MLOps practices and tools.
• Solid experience spanning the entire development stack, including Python, Docker, Kubernetes, and cloud platforms such as AWS, Azure, or GCP, confident in abilities to deliver cutting-edge solutions.
• Experience with modeling and implementing deep learning models by employing TensorFlow or PyTorch.
• Knowledge of pipeline and workflow management tools (Airflow, Argo Workflows, etc.).
• Experience with CI/CD tools (Jenkins, Travis, Argo CD, Terraform, etc.).
• An independent, problem-solving approach, paired with a passion for data and a growth-mindset ready to tackle genuine challenges.
• Able to collaborate effectively in cross-functional teams.

What Would Be Nice to Have

• 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.

About Domyn

Domyn is a company specializing in the research and development of Responsible AI for regulated industries, including financial services, government, and heavy industry. It supports enterprises with proprietary, fully governable solutions based on a composable AI architecture — including LLMs, AI agents, and one of the world’s largest supercomputers.