Job Description :

About the Job :

- Design, code, test, debug, and document software in compliance with client standards, policies, and procedures.

- Analyze business needs and create effective software solutions.

- Prepare design documentation and develop test data for unit, string, and parallel testing.

- Evaluate and recommend software and hardware solutions to meet business requirements.

- Troubleshoot and resolve customer issues with software solutions while implementing improvements and enhancements.

- Collaborate with business and development teams to clarify requirements and ensure testability.

- Draft, revise, and maintain test plans, test cases, and automated test scripts.

- Execute test procedures, log defects, recommend corrective actions, and retest to confirm resolution.

- Document testing procedures for repeatability and knowledge sharing.

- Conduct performance and scalability testing as needed.

Essential Job Functions :

- Lead small to moderately scoped projects, including supervision of junior team members when required.

- Provide solutions to a diverse range of complex technical challenges.

- Manage schedules, costs, and documentation to drive projects to successful completion.

- Mentor, assign, and review the work of less experienced developers.

- Perform estimation efforts and track progress for assigned projects.

- Draft and execute test plans/scripts with a focus on end-to-end system flows.

- Perform root cause analysis of defects, define corrective actions, and communicate results effectively.

Qualifications :

Essential Requirements :

- Proficiency in Python 3.x.

- Basic understanding of Natural Language Processing (NLP).

- Experience designing and building NLP models such as Text Classifiers, Recommenders, and Conversational Agents.

- Familiarity with Embeddings and Vector Databases.

- Understanding of Language Models.

- Experience with GenAI frameworks (e.g., Retrieval Augmented Generation - RAG).

- Experience designing and building inference APIs using Python frameworks like FastAPI, Flask, or Django.

- Experience with Relational and Non-Relational Databases.

- Knowledge of LLMOps stacks such as LangChain or LlamaIndex.

Good to Have

- Hands-on experience with fine-tuning LLMs, deployments, and MLOps.

- Deep understanding of Python development stack, ecosystems, and libraries:

- NLTK, RASA, LangChain, NumPy, SciPy, Pandas, Dask, spaCy, scikit-learn, PyTorch, TensorFlow.

- Experience in GenAI model evaluation, fine-tuning, and deployments.

- Familiarity with Python testing frameworks (e.g., Pytest, unittest).