AzureCloudPythonAIDeep LearningGenerative AILangChainAgenticAutoGenGitVersion Control
About this role
Role Overview
Deliver production-quality solutions for data extraction, classification, triaging, routing, search, and agentic workflow orchestration
Design, build, and optimize agent-based systems that can plan, reason, and execute multi-step tasks using tools and APIs
Programmatically explore data, derive insights that are statistically sound, and convey findings to colleagues of varying sophistication
Develop and maintain workflow pipelines that integrate LLMs, external tools, and business logic for scalable automation
Label and validate datasets of various sizes, using manual methods as well as programmatic and AI-driven approaches
Evaluate the performance of models and end-to-end agentic systems using practical and statistical benchmarks
Collaborate with other scientists, engineers, product owners, and business customers to develop solutions that meet the business problem
Create, contribute to, improve, and convey technical and non-technical documentation of solutions
Requirements
Experience applying quantitative methods in a corporate environment
Experience with Python from a functional programming paradigm, able to manage dependencies, virtual environments, and version control in git
Experience with cloud computing platforms such as Azure
Expertise in supervised and unsupervised learning along with experience in deep learning and transfer learning
Experience designing and implementing agentic workflows, including chaining, tool usage, memory management, and decision logic
Experience working with generative AI and foundation models (e.g., GPT-4o, Mistral), including prompting, orchestration, and evaluation of agent behaviors
Experience developing solutions from inception through deployment
Graduate degree in a quantitative field
Experience with sequential algorithms (e.g., LSTM, RNN, GRU, etc.)
Experience building or contributing to agent frameworks (e.g., LangChain, Semantic Kernel, AutoGen, or similar orchestration layers)
Experience evaluating ethical implications of AI and considerations around controlling them