Top Tech Jobs & Startup Jobs

The Azure DevOps Engineer will design and implement a secure Azure environment, focusing on governance, security, networking, and infrastructure using IaC, ensuring readiness for application development.

Lead cloud and integration architecture end-to-end for production AI systems: design secure AWS-hosted services, define integration contracts and patterns, guide implementation, unblock developers, coordinate with client architects and vendors, maintain architecture governance and delivery progress.

Design, deploy, and govern enterprise-scale data architectures and platforms to support analytics and AI. Define modeling standards, integration pipelines, data quality, lineage, and security. Lead technical direction, mentor engineers, evaluate AI tooling, and support proofs of concept and solution roadmaps that enable generative AI and RAG solutions.

Lead Salesforce solution architecture for Quote-to-Cash and services automation. Design integrations with ERP/HCM/billing, set governance and standards, recommend AppExchange tools, drive AI-native delivery, and mentor delivery teams to implement scalable Salesforce-based professional services solutions.

Design, build, and operate scalable data pipelines and platforms (Snowflake, Databricks, Delta Lake). Implement dbt models, semantic layers, data quality, orchestration (Airflow/Dagster/ADF), and DevOps for data. Build AI-enabled pipelines for RAG, embeddings, vector stores and integrate LLMs into ETL. Ensure reliability, monitoring, and cost-effective cloud architectures across AWS and Azure.

In this role, you'll manage NetSuite day-to-day operations, support users, optimize configurations, and ensure data quality within financial processes.

Drive revenue by selling AI solutions and consulting services to PE portfolio companies and Fortune 1000 accounts while managing complex sales cycles and building relationships with decision-makers.

The AI Developer will design, implement, and deploy AI agents and workflows, integrating advanced models and ensuring reliable performance in production environments.

The AI Software & Data Engineer will design and build full-stack systems, data platforms, and AI prototypes, integrating AI capabilities for enterprise solutions.

The Full Stack Data Engineer will design and build scalable data pipelines, optimize Snowflake architecture, develop dashboards and analytics solutions, and collaborate with cross-functional teams to ensure data reliability and meet business requirements.