Top Tech Jobs & Startup Jobs

Design, deploy, and operate large-scale distributed systems. Manage Kubernetes, Istio, Linux, and observability (Prometheus/Grafana/Loki). Automate with Go/Python/Shell, use Terraform for IaC, troubleshoot networking/storage, support AI/ML infrastructure, and participate in on-call rotations and postmortems to improve reliability.

Provide Oracle and PostgreSQL database consulting, including solution design, administration, backup and disaster recovery, migrations, monitoring, performance optimization, troubleshooting, and infrastructure improvement. Manage client commitments, reporting, documentation, change controls, and technical communication. Participate in on-call rotations and process-improvement initiatives. Support cloud and on-premises database environments across AWS, Google Cloud, and Azure.

Provide Oracle and PostgreSQL database consulting, including solution design, administration, backup and disaster recovery, migrations, monitoring, performance tuning, troubleshooting, and infrastructure improvements. The role involves client communication, technical documentation, process improvement, automation, cloud database support, and participation in an on-call rotation.

Provides Oracle and PostgreSQL database consulting, including solution design, administration, upgrades, backup and disaster recovery, replication, migrations, performance tuning, monitoring, troubleshooting, and data architecture. Advises clients on infrastructure improvements, documents action plans, prepares reports, supports incident and problem management, and participates in process improvement initiatives and an on-call rotation. The role also involves database migrations between on-premises and cloud environments across AWS, Google Cloud, and Azure.

Provides Oracle and PostgreSQL database consulting, administration, architecture, migrations, backup and disaster recovery, monitoring, performance optimization, and troubleshooting. Designs and implements database infrastructure, supports cloud and on-premises environments, develops automation and action plans, maintains documentation, participates in on-call rotations, and communicates directly with clients. The role also contributes to process improvements and supports migrations across Oracle, MySQL, SQL Server, and PostgreSQL using cloud and change-data-capture tools.

Design, deploy, and operate large-scale distributed systems. Operate Kubernetes clusters and Istio, automate workflows with Go/Python/shell, build observability with Prometheus/Grafana/Loki, troubleshoot networking/storage/performance, support AI/ML infrastructure, and participate in on-call rotations and postmortems to improve reliability.

Design and develop cloud-based data platform solutions, including data pipelines, ingestion, transformation, cleansing, integrations, and data applications. Translate technical requirements into detailed designs, write reliable code, develop test automation, troubleshoot operational issues, tune batch and real-time processing, secure cloud data platforms, and implement CI/CD and monitoring. The role also involves advising client developers and defining efficient operational processes.

Own end-to-end data platform architecture across ingestion, lakehouse, warehouse, transformation, modeling, governance, and analytics delivery. Build pipelines, Spark and SQL transformations, data models, and production code. Design Databricks or Microsoft Fabric lakehouses, implement Delta Lake and medallion architecture, establish access controls and governance, and integrate databases, SaaS applications, APIs, files, and legacy systems. Evaluate platform choices based on client workloads, licensing, skills, and cost.

Develop, deploy, and maintain scalable AI/ML pipelines and production models, including LLMs and generative AI. Optimize model performance, latency, and cost across AWS, GCP, and Azure. Apply MLOps practices such as CI/CD, versioning, monitoring, logging, and maintenance. Collaborate with data scientists, software engineers, solution architects, and cross-functional teams to integrate AI capabilities into products and workflows.

Lead the architecture and development of scalable AI/ML pipelines and production systems, including LLMs and Generative AI. Mentor engineering teams, guide technical decisions, operationalize models, optimize performance and costs, and implement MLOps practices such as CI/CD, monitoring, versioning, and maintenance. Partner with executives, clients, product managers, data scientists, and software engineers to align AI roadmaps with business goals and integrate ethical AI capabilities into enterprise applications.