We are seeking a highly motivated and experienced AI/ML Developer Level II to join our dynamic
team. In this role, you will be a key contributor to the design, development, and deployment of
sophisticated conversational AI systems, primarily using the RASA framework. Your deep
expertise in Python, coupled with hands-on experience in the Google Cloud Platform (GCP)
ecosystem, will be essential for building, scaling, and maintaining robust, enterprise-grade virtual
assistants and chatbots. You will move beyond prototyping to take ownership of components,
optimize model performance, and ensure the reliability of our AI solutions in production.
Key Responsibilities:
(Must-have)
agents using the RASA Open Source and/or RASA X/Pro platforms. This includes developing complex dialogue management with stories and rules, configuring the NLU pipeline, and creating custom actions.
models. Implement strategies for continuous improvement using conversation analytics
and user feedback to enhance intent classification, entity recognition, and response quality.
custom actions, policies, and integrations. Develop scalable backend services and APIs to connect RASA agents with other business systems.
RASA bots on GCP (using Google Kubernetes Engine - GKE, Pub/Sub for messaging, Cloud
Run, or Compute Engine). Utilize GCP services like Vertex AI and Dialogflow CX for complementary use-cases or hybrid architectures, and Cloud Speech-to-Text / Text-to-Speech for voice-enabled bots.
Nice-to-have:
and deployment of RASA models using tools like Git. Champion MLOps best practices for
versioning, monitoring, and retraining models.
deriving insights. Use Cloud Storage for managing training data and model artifacts.
Required Qualifications:
related field, or equivalent practical experience.
years of hands-on, in-depth experience building and deploying production-level chatbots
with the RASA framework.
engineering principles, design patterns, and API development.
detection, entity extraction, context management) and practical experience with machine
learning libraries (e.g., scikit-learn, spaCy, Transformers).
Soft Skills & Other Requirements:
troubleshoot complex technical issues in distributed systems.
from conception to deployment and beyond, working with minimal supervision.
articulate technical concepts to both technical and non-technical stakeholders.
share knowledge with the team.
Preferred Qualifications (Bonus):
