Professional Summary
Generative AI Engineer with 7 years of experience architecting large-scale natural language processing systems and improving model reliability through rigorous CI/CD practices. Specialises in AWS and GCP infrastructure, having shipped user-facing features that serve millions of requests daily. Passionate about balancing innovation and operational excellence in AI product development.
Skills
- AWS
- Python
- GCP
- NLP
- Typescript
- Terraform
- Ci/Cd
- Leadership
- Docker
- Github Actions
- Azure
- Communication
- Machine Learning
- Kubernetes
Experience
Generative Ai Engineer — MNC Software
- Architected generative text pipeline serving 10M daily API calls with 99.95% uptime.
- Implemented observability stack reducing incident MTTR from 8 hours to 1 hour.
- Migrated model training workflows from on-premise to AWS, cutting compute costs by 40%.
- Improved test coverage across NLP services from 70% to 92% with policy-driven automation.
- Coached cross-functional teams on AI ethics best practices for customer-facing features.
AI Research Engineer — EXL
- Designed conversational AI models reducing support escalation rates by 30%.
- Orchestrated Kubernetes clusters for secure, compliant model inference pipelines.
- Established CI/CD patterns for ML experiments, boosting deployment velocity by 50%.
- Published findings on explainable AI frameworks in peer-reviewed machine learning journals.
- Drove NLP hackathons that accelerated internal prototyping and proof-of-concept cycles.
Education
M.S. Computer Science
University of California, Berkeley
Certifications
- AWS Certified Machine Learning - Specialty
- TensorFlow Developer Certificate