Senior Gen AI Engineer (R-18985)
Eyeota
Key Responsibilities:
- Work on development of B2B Risk solutions which includes Standard and custom solutions catering to various clients including fortune 500 companies
- Work with internal / external D&B clients and stakeholders; Participate in all aspects of a modelling engagement, including design, development, validation, calibration, documentation, approval, implementation, monitoring, and reporting
- Ability to applying LLMs, and prompt engineering to analyze large-scale, unstructured and structured B2B datasets (e.g., Company News, Corporate Annual Reports) for credit risk, fraud detection, and compliance.
- Design, develop and test new risk signals to effectively identify risk patterns from structured and Unstructured data
- Serve as a Subject Matter Expert on risk models within the Analytics team and with business users; consult with the business, as appropriate, on predictive modelling solutions
- Develop AI Agents for business risk monitoring, deploying autonomous agents. These agents utilize Machine Learning (ML) and Natural Language Processing (NLP) to detect risk triggers, anomalies in real-time, shifting risk management from reactive reporting to predictive, actionable insights
- Ability to manage multiple assignments, many of which with challenging timelines
- Ability to work independently, as well as collaborate effectively in a team environment
- Partner with internal D&B team to develop new business solutions in risk analytics
Key Skills:
- Hands-on experience with Generative AI / Large Language Models (LLMs)
- Strong knowledge of prompt engineering, prompt chaining, and structured LLM outputs
- Experience building LLM-powered applications using RAG (Retrieval-Augmented Generation) patterns
- Ability to design and develop AI / Agentic AI solutions, including Autonomous or semi-autonomous agents, Multi-step workflows and decision orchestration, Real-time signal detection and alerting
- Experience applying NLP techniques for processing unstructured data (news, reports, filings)
- Familiarity with agent frameworks (e.g., LangChain, LangGraph or equivalent) is a strong plus
- Understanding of LLM evaluation, grounding, explainability, and risk controls
- Master’s degree or higher with concentration in a quantitative discipline such as (Math/Stat, Economics, Computer Science, Finance, Operations Research, etc.) with 5 - 8 years of experience in Data Science.
- Proven experience on design and development of Risk models and frameworks
- Experience in design and development of risk models is desirable.
- Strong experience in Scorecard Development, application of Machine Learning Models using techniques such as Xgboost, Light GBM, Random Forest, Logistic Regression, Decision Tree, Neural Networks etc.,
- Strong programming skills with the ability conduct research utilizing Python and Pyspark to manipulate data and conduct statistical analysis
- Strong SQL skills and experience working with large datasets
- Strong client collaboration skills, including the ability to build and maintain relationships with clients
- Ability to effectively communicate complex ideas to both a technical and non-technical audience
- Strong analytical mind and business acumen, especially in Financial Services Industry
- Proven working experience in applying modern machine learning techniques
- Passionate on stay abreast of cutting-edge ML algorithms, with good grasp of ML explain-ability methods
- Strong technical writing skills
- Familiarity with processing of unstructured data is a plus
- Experience in NLP / LLMs is mandatory
Generative AI & Agentic AI Skills:
What we are looking for:
Preferred Skills:

