Top Tech Jobs & Startup Jobs

Develops production-grade Salesforce solutions using Apex, Lightning Web Components, Flow, and integrations. Responsibilities include implementing custom business logic, user interfaces, automation, REST/SOAP integrations, data and sharing models, troubleshooting, and source-driven Salesforce DX development while maintaining platform limits and long-term maintainability.

Develop and maintain ServiceNow solutions across ITSM, ITOM, HRSD, CSM, and custom applications. Responsibilities include platform configuration, JavaScript scripting, workflows, integrations, scoped application development, portals, CMDB improvements, reporting, troubleshooting, upgrades, testing, documentation, and stakeholder collaboration. The role requires strong ServiceNow development expertise, REST/SOAP integration experience, Flow Designer and IntegrationHub knowledge, Service Portal development, CMDB understanding, and ServiceNow certification.

Develop and configure Workday solutions across HCM and Finance, including advanced reports, calculated fields, business processes, condition rules, security, integrations, tenant management, and release support. Translate stakeholder requirements into maintainable platform solutions, troubleshoot issues, participate in design and code reviews, and mentor junior engineers. Preferred work includes Workday Extend development, PRISM data modeling, multi-region deployments, and Payroll or Financials support.

Designs, deploys, automates, and operates enterprise VMware virtualization, software-defined networking, and storage platforms across on-premises and hybrid-cloud environments. Responsibilities include managing vSphere, vSAN, NSX, Aria, and Tanzu; capacity planning; disaster recovery and SRM; troubleshooting compute, network, and storage layers; and supporting automation and cloud migration initiatives.

Designs, builds, and operates large-scale Hadoop-based data pipelines and analytics platforms. Responsibilities include ingesting, transforming, and analyzing structured and unstructured data; developing Spark applications; managing streaming and distributed data systems; orchestrating workflows; troubleshooting production environments; and delivering reliable, performant, cost-effective platforms supporting analytics, machine learning, and reporting.

Define and lead enterprise data platform architecture across ingestion, storage, processing, governance, and consumption. Establish standards for data modeling, security, lineage, data contracts, and lifecycle management. Architect lakehouse, warehouse, and streaming solutions; guide architecture reviews; optimize cost, capacity, availability, and disaster recovery. Partner with engineering, ML, BI, product, and business teams while mentoring data engineers and architects and producing architecture documentation.

Build and operate petabyte-scale data infrastructure for AI training, evaluation, and continual improvement. Responsibilities include multimodal data ingestion, cleaning, deduplication, quality assurance, dataset versioning, lineage, high-throughput loading, labeling workflows, storage architecture, privacy controls, observability, and cost optimization. The role partners with ML researchers and engineers while maintaining reproducible, reliable, and efficient data pipelines.

Design, operate, and optimize large-scale AI infrastructure for GPU-based training and inference. Responsibilities include distributed scheduling, high-performance storage and networking, observability, fault tolerance, security, automation, cost optimization, and developer tooling across on-premises, cloud, and hybrid environments. The engineer partners with ML and research teams on capacity planning and platform reliability.

Designs and maintains large-scale Terraform infrastructure-as-code across cloud and hybrid environments. Responsibilities include building reusable modules, managing state, implementing CI/CD pipelines and policy-as-code, supporting multi-account and multi-cloud provisioning, testing infrastructure, embedding security guardrails, migrating legacy infrastructure, optimizing costs, and mentoring engineering teams. The role also requires documentation, runbooks, architecture diagrams, and evaluation of Terraform and OpenTofu ecosystem developments.

Designs, operates, and scales enterprise observability platforms for metrics, logs, traces, events, and synthetic monitoring. Establishes instrumentation, SLO, SLI, error-budget, dashboard, and alerting standards; manages telemetry storage, cost, and signal quality; integrates observability with CI/CD, incident response, and progressive delivery. The role also develops self-service tooling, supports distributed tracing, evaluates open-source and commercial tools, mentors engineering teams, and maintains documentation and runbooks.