Teams at Dysrupit

Build and productionize AI/ML, Generative AI, and agentic solutions on Databricks. Develop feature, training, and serving pipelines; create RAG systems and reusable accelerators; optimize jobs and workflows; and support governed, scalable production deployments. Collaborate directly with data scientists, architects, client engineering teams, and stakeholders to gather requirements, troubleshoot issues, and deliver documentation and runbooks.

Build and maintain Python services, APIs, configuration workflows, and reporting outputs for a GCP-based data platform. Responsibilities include managing versioned Firestore data, syncing to BigQuery, generating Excel reports, deploying services with Cloud Run and Cloud Storage, provisioning infrastructure with Terraform, maintaining CI/CD pipelines, applying IAM best practices, testing, troubleshooting, and collaborating with data engineers and stakeholders.

Leads technical solutioning and delivery for data and AI engagements, including discovery, target-state architecture, proposals, proofs of concept, Databricks lakehouses, production generative AI systems, CI/CD, infrastructure as code, testing, observability, and cost optimization. Provides hands-on implementation, client enablement, executive presentations, mentoring, production handover, and development of reusable architectures and accelerators. The role may also help recruit and lead a small delivery team.