Jobs at Zefr

Manage client relationships for Zefr’s programmatic advertising product. Guide brands and agencies in executing campaigns, optimizing performance, meeting KPIs, and resolving technical or strategic challenges. Analyze client data, provide consultative advice, communicate customer needs to product teams, identify expansion opportunities, and deliver an excellent customer support experience.

Develop and maintain code-based automated tests for APIs, web applications, data pipelines, AI/ML services, and partner integrations. Plan feature testing, validate data and model outputs, integrate reliable test suites into CI/CD, monitor production quality, investigate incidents, and verify releases. Collaborate with engineering, product, data science, and customer-facing teams while improving test coverage, reliability, and performance.

Support and improve cloud infrastructure, Kubernetes-based microservices, CI/CD pipelines, infrastructure-as-code, observability, and production reliability. The role involves debugging application and infrastructure issues, participating in a 24/7 on-call rotation, maintaining documentation and runbooks, and collaborating with engineering and data science teams to deliver scalable, automated systems.

Design, build, and operate complex Apache Airflow workflows, Snowflake and dbt data transformation pipelines, and distributed data science inference systems across multi-cloud environments including AWS and GCP. Collaborate with an experienced data engineering team while applying systems engineering and product lifecycle principles.

Annotate and evaluate videos, images, and metadata across major social platforms to support AI system training. Apply contextual and cultural guidelines, resolve ambiguous or sensitive content decisions, perform quality assurance, identify trends and edge cases, conduct root cause analysis, prepare weekly reports, and recommend improvements to labeling processes and tools. The role requires English and Hindi fluency, strong attention to detail, analytical judgment, and comfort handling sensitive content.

Design, implement, and operate cloud-native microservices in Kubernetes; ensure scalability, reliability, observability, and incident response; use AI tools daily for coding and research; collaborate with product, ML, and infra teams; contribute to architecture and standards; mentor engineers and drive projects to production.