AgileEngine - Team Lead - NLP

Key Responsibilities :

- Lead a team of AI/ML engineers and data scientists in designing, developing, and deploying intelligent data platforms.

- Architect and deliver modular, AI-enabled solutions for document ingestion, extraction, and validation workflows.

- Integrate LLM/GenAI-based features to automate data processing, prioritization, and explainability.

- Oversee the end-to-end development lifecycle - from data exploration and modeling to production deployment.

- Collaborate closely with stakeholders to define objectives, set priorities, and ensure timely, high-quality delivery.

- Promote a culture of proactive communication, continuous improvement, and accountability within the team.

- Apply best practices in software engineering including Test-Driven Development (TDD), refactoring, and design patterns.

- Manage CI/CD pipelines and ensure smooth integration with cloud-based environments (Azure or GCP).

- Contribute to building self-service capabilities for clients - enabling self-onboarding, data monitoring, and pipeline configuration.

- Stay current with emerging trends in AI, NLP, and Agentic AI architectures to guide innovation initiatives.

Must-Have Skills & Qualifications :

- Bachelor's or Master's degree in Computer Science, Mathematics, Engineering, or a related field.

- Demonstrated team leadership experience, managing AI/ML or data engineering teams in fast-paced environments.

- Proven ability to lead complex projects, manage deliverables, and communicate effectively with stakeholders.

- Strong hands-on expertise in Python and Natural Language Processing (NLP).

- Experience in data exploration, data mining, visualization, and building statistical/machine learning models.

- Practical experience in developing and deploying AI/ML solutions into production environments.

- Familiarity with Large Language Models (LLMs), LangChain, LangGraph, and Agentic AI frameworks (a strong plus).

- Understanding of text processing and document automation workflows.

- Solid understanding of software development best practices - TDD, code refactoring, pair programming, and modular design.

- Experience with cloud platforms, preferably Azure or Google Cloud Platform (GCP).

- Knowledge of DevOps practices and CI/CD pipelines for AI/ML deployment.

- Highly self-motivated, proactive, and results-driven, with a strong sense of ownership and delivery focus.

Nice-to-Have Skills :

- Knowledge of the financial industry, especially Private Assets and related ecosystems.

- Experience with data validation, auditability, and explainable AI (XAI) frameworks.

- Exposure to AI-driven workflow automation and document intelligence solutions.

About the Platform/Project :

- You will lead the development of a modular, AI-enabled platform that supports end-to-end document and data workflows, enabling:

- Automated ingestion, extraction, and validation of fund- and asset-level documents.

- Self-service onboarding and monitoring of data completeness by clients.

- Configurable delivery pipelines for flexible data operations.

- Integration of LLM and GenAI features for automation, prioritization, and explainability.