Top Tech Jobs & Startup Jobs

Develop and maintain enterprise AEM solutions across Sites, Assets, and Cloud Service. Build components, templates, workflows, OSGi services, Sling models, Java backends, and front-end experiences. Implement headless delivery, GraphQL, personalization, integrations, performance optimization, Dispatcher configuration, and CI/CD pipelines. Troubleshoot production issues and collaborate with content authors, designers, product owners, and infrastructure teams while documenting standards and technical decisions.

Develop and support SAP S/4HANA enhancements, integrations, reports, and custom applications throughout the development lifecycle. Responsibilities include requirements analysis, technical design, ABAP and ABAP OO coding, CDS views, AMDPs, OData services, Fiori integration, unit testing, performance tuning, troubleshooting, documentation, and post-go-live support. The role requires collaboration with functional consultants and business stakeholders while applying clean-core principles and supporting SAP enterprise landscapes.

Lead enterprise ServiceNow architecture across ITSM, ITOM, HRSD, CSM, SecOps, GRC, and custom applications. Establish platform governance, data and CMDB standards, integration patterns, security models, workflow practices, upgrade strategies, and performance improvements. Partner with stakeholders on platform roadmaps, mentor technical teams, support compliance, and produce durable architecture documentation. The role requires extensive ServiceNow architecture experience, broad module expertise, integration and security knowledge, and relevant certifications.

Embed security throughout the software development lifecycle by conducting application security reviews, identifying vulnerabilities, integrating SAST, DAST, and SCA tools into CI/CD, and partnering with engineering teams to build secure systems. The role requires code review across multiple languages, cloud security knowledge, authentication and cryptography expertise, security automation, and strong communication. Preferred experience includes offensive security, red-team operations, bug bounties, CVEs, AI/LLM security, and regulated industries.

Designs, builds, and operates SAP BTP extensions, side-by-side applications, and integration solutions for SAP S/4HANA and other SAP applications. The role focuses on clean-core extension patterns, CAP development, Fiori/UI5, OData services, BTP runtimes and services, identity, CI/CD, integration, analytics, and AI capabilities.

Designs and maintains scalable Terraform infrastructure across cloud and hybrid environments. Builds reusable modules, automation pipelines, policy-as-code controls, state-management strategies, and infrastructure testing. The role supports multi-account and multi-cloud provisioning, security guardrails, migrations to infrastructure as code, cost governance, documentation, troubleshooting, and team mentorship.

Develop and customize Guidewire InsuranceSuite solutions for insurance carriers, including Gosu development, product model and rule configuration, integrations, database work, and Guidewire Cloud upgrades. The role requires production Guidewire experience across PolicyCenter, BillingCenter, or ClaimCenter, collaboration with business and technical stakeholders, code and design reviews, troubleshooting, and mentoring junior engineers.

Design, optimize, and deploy machine learning models for mobile, embedded, and specialized edge hardware. Apply quantization, pruning, distillation, and hardware-aware optimization to improve latency, energy efficiency, and memory usage. Build cross-platform inference runtimes, hybrid edge-cloud architectures, secure model update workflows, privacy-conscious telemetry, and benchmarking systems. Collaborate with hardware, firmware, and product teams while maintaining technical documentation and evaluating emerging edge AI technologies.

Build and operate large-scale data infrastructure for AI training and evaluation pipelines. Responsibilities include data ingestion, transformation, quality assurance, lineage, versioning, reproducibility, and high-throughput delivery across multimodal datasets. The role requires operating petabyte-scale systems, applying distributed systems and data modeling expertise, supporting accelerator-based training, and following strong software engineering practices including testing, CI/CD, and code review.

Designs, operates, and scales AI infrastructure for GPU-based training and inference. Responsibilities include distributed training platforms, scheduling, storage and networking performance, observability, fault tolerance, cost optimization, security, automation, and developer tooling. Partners with ML and research teams on capacity planning and maintains reliable hybrid cloud and on-premise infrastructure.