Data Engineer

AIML, Machine Learning & Data Science.
• Large Language Models(GPT, Claude), Generative AI, Retrieval Augmented Generation.
• Agentic AI, CoPilot, MCPs.
• AIML Algorithms(Regression, Classification, Decision Trees, KNN, K-Means)
• Python (NLTK, NumPy, Scikit-learn, Pandas)

Candidates will be expected to work on developing & implementing AIML Solutions for Test Automation in the Securities Processing space. This will entail building AIML Solutions for Test Generation, Test Prioritization, Defect Triage/Reporting, Code Coverage, Framework Migration/Setup. The role requires experience in AIML(LLMs, Gen AI & Agentic AI) & Python.

The role will require proficiency in all aspects of AIML & Software Development including:
• Knowledge of AIML & Python is must.
• Ability to develop and implement Generative AI & Retrieval Augmented Generation solutions focused on software testing.
• Experience with Large Language Models(GPT, Claude).
• Hands- on experience with GitHub Copilot.
• Must be a regular user of Agentic AI solutions and MCPs.
• Deployment experience with Docker & Kubernetes to deploy the AIML solutions is good to have.
• Front End experience in React to build front end for the AIML solutions is a plus.
• Hands- on experience with Python libraries like(NLTK, NumPy, Scikit-learn, Pandas).
• Knowledge of AIML algorithms (Regression, Classification, Decision Trees, KNN, K-Means) is preferred.
• Experience with building, training & finetuning AIML models is a plus.
• Bachelor’s degree in Computer Science or related field of study or equivalent relevant experience; demonstrated experience of Data Science & AIML with focus on quality assurance solutions.
• Lifecycle principles and quality assurance processes and methodologies.
• Experience with automated testing with good understanding of test automation frameworks.
• Good grasp of SQLs.
• Experience of working in an Agile environment, participating in sprint planning, backlog refinement, and retrospectives.
• Must have excellent verbal and written skills being able to communicate effectively on both a technical and business level