About the Role

We are seeking an experienced AI/ML Developer Level II to join our Innovation & Software Solutions team. In this role, you will be responsible for designing, developing, deploying, and optimizing enterprise-grade conversational AI solutions using the RASA framework, Python, and Google Cloud Platform (GCP). Working closely with cross-functional teams, you will build scalable, production-ready virtual assistants and intelligent automation solutions while driving continuous improvements in machine learning models, NLP performance, and MLOps practices. This is an excellent opportunity for a proactive developer who is passionate about conversational AI, cloud technologies, and delivering innovative AI-powered solutions at scale.

Responsibilities:

Design, develop, and maintain enterprise-grade conversational AI solutions using RASA Open Source and RASA Pro/X.
Develop complex dialogue flows, NLU pipelines, custom actions, stories, and rules.
Train, evaluate, fine-tune, and optimize NLP models to improve chatbot performance, intent recognition, entity extraction, and user experience.
Build clean, scalable, and maintainable backend services and APIs using Python.
Deploy, monitor, and manage AI applications on Google Cloud Platform (GKE, Cloud Run, Compute Engine, Pub/Sub, Vertex AI, Dialogflow, Cloud Speech-to-Text, and Text-to-Speech).
Integrate conversational AI solutions with enterprise systems and third-party services.
Contribute to CI/CD pipelines, automated testing, model versioning, and MLOps best practices.
Analyze conversational data using BigQuery and leverage Cloud Storage for managing training datasets and model artifacts.
Collaborate within an Agile development environment and mentor junior team members when needed.

Qualifications:

Bachelor's degree in Computer Science, Software Engineering, Data Science, or a related discipline, or equivalent practical experience.
Strong hands-on experience with Python and software engineering best practices.
Proven experience developing conversational AI solutions using RASA.
Hands-on experience with Google Cloud Platform (GCP) services.
Strong understanding of Natural Language Processing (NLP) concepts, including intent classification, entity recognition, dialogue management, and context handling.
Experience working with machine learning frameworks such as spaCy, scikit-learn, or Transformers.
Proficiency with Git and collaborative software development workflows.
Excellent analytical, problem-solving, and communication skills.

Preferred Skills:

Experience with Docker and Kubernetes.
Knowledge of Terraform or other Infrastructure-as-Code tools.
Experience implementing CI/CD pipelines and MLOps workflows.
Google Cloud certifications, particularly Professional Machine Learning Engineer, are highly desirable.