Note: The job is a remote job and is open to candidates in USA. Domyn is a company specializing in the research and development of Responsible AI for regulated industries, including financial services. They are hiring a Senior AI Engineer to lead the engineering and deployment of AI solutions for financial workflows, requiring expertise in building scalable AI systems and collaborating with cross-functional teams.
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
Skills
- 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
- Additionally, 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
- 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
Benefits
- Competitive compensation structure
- Performance-based bonuses
- Comprehensive benefits as part of the total compensation package
Company Overview