Data Engineer with AIML(LLM, Agentic AI) & Python experience

• 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.