Lead technical hiring process, developer onboarding, code reviews, architectural discussions, daily standups, SDLC enforcement, dev environment standardization, and mentorship programs

Foster culture applying DevOps best practices, including CI/CD pipelines, automated testing, and monitoring/alerting

Productize generally useful features, grow data platform, standardize internal data model, and package common code

Adapt cloud infrastructure to support product growth while maintaining performance and minimizing costs

Develop web apps in React + Flask for customer decision support, task prioritization, analytics, and data capture

Integrate with enterprise data warehouses, ERPs, CRMs, third-party APIs, and miscellaneous data silos. Build and maintain complex Python data pipelines powering user-facing dashboards and automated outreach systems

Build custom datasets on proprietary data to develop applied AI/ML models, deploying using MLOps best practices

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Built manual review dashboard to streamline internal recruiter team workflows and automate ML dataset expansion

Engineered data pipelines and set up cloud infrastructure (e.g. Airflow) for sourcing jobs, extracting features from candidate resumes and job descriptions, making recommendations, and submitting & tracking job applications

Built integrations with job boards and applicant tracking systems. Built and maintained Stella's internal data model

Innovated foundational AI/ML recommender systems, directly accounting for 30% of hires facilitated by Stella

Wrote back-end functionality for these interfaces in Java, serving this functionality via RESTful API endpoints (via JAX-RS)

Wrote Python and Javascript code for MongoDB migrations