Jobs at Integrant

Lead Java full-stack engineer responsible for designing, developing, testing, and deploying microservices-based applications. Lead and coach the technical team, perform code reviews, define architecture, estimate work, manage releases and configuration, and interface with PMs and clients while promoting Agile practices and quality standards.

This role combines SysOps and DevOps, focusing on client-facing presales and technical execution. The candidate will design and maintain complex GPU and HPC environments, optimize Kubernetes clusters, and lead architecture decisions for robust solutions, requiring significant experience in Linux systems and infrastructure engineering.

Manage and maintain storage environments using Weka and Ceph, provision resources, implement data protection strategies, and troubleshoot issues in AI and HPC contexts.

The role involves leading technical projects, overseeing architecture, driving engineering excellence, mentoring team members, and ensuring high-quality software delivery.

Lead design, development, deployment, and monitoring of ML and generative AI solutions (including RAG and agentic systems). Drive MLOps best practices, cloud deployments, model monitoring, research, and client-facing engagements while mentoring junior team members and shaping AI strategy.

Lead design, development, deployment, and monitoring of ML and Generative AI solutions (including RAG and agentic systems). Mentor team members, engage clients, conduct research, implement MLOps, and productionize scalable AI applications.

Lead a team building scalable microservices: design, develop, test, deploy, and maintain Java/Spring applications on cloud. Coach engineers, conduct code reviews, drive architecture, estimate work, manage releases, and liaise with the PM and clients.

The Head of Marketing & Demand Generation will lead marketing efforts for lead generation in the U.S. and European markets, oversee a marketing team, design campaigns, manage the pipeline, and collaborate with technical leadership.

The Lead Software Engineer will develop and maintain front-end applications using Angular and JavaScript, ensuring high quality and performance while collaborating with back-end developers and mentoring junior engineers.

Lead design, development, and maintenance of end-to-end analytical solutions on Microsoft on-premises and Azure cloud. Elicit requirements, mentor junior engineers, deliver analytical and real-time solutions (ETL, data lake/warehouse, governance), and transfer knowledge to clients.

The Principal DevOps/SysOps Engineer leads the deployment, configuration, and maintenance of servers, manages clusters using containerization and cloud technologies, and ensures system health through monitoring and troubleshooting.

Lead architecture, operations, and performance tuning of Ethernet and InfiniBand fabrics in an HPC/AI data center. Own fabric design, lifecycle management, monitoring, incident response, diagnostics, automation, and documentation. Collaborate with platform, storage, and software teams, participate in on-call rotation, and lead design reviews and knowledge-sharing to ensure low-latency, high-bandwidth network performance.

The Executive Assistant supports the VP of International Operations, managing calendars, coordinating tasks, conducting research, and enhancing productivity through modern tools and AI.

The Principal DevOps Engineer will design and implement CI/CD pipelines, utilize monitoring tools, manage cloud solutions, and apply infrastructure-as-code practices.

Manage and administer enterprise storage infrastructure (DDN, VAST, Pure), including provisioning, configuration, performance monitoring, backups/replication, troubleshooting, documentation, and customer-facing support. Maintain SAN/NAS, storage pools/volumes/snapshots, perform routine maintenance, participate in on-call rotation, and support HPC and cloud-integrated storage solutions.

The Senior Technical Project Lead will manage project delivery, coordinate team activities, ensure quality software delivery, and maintain effective communication with stakeholders.

The Lead AI Platform Engineer optimizes AI workloads on GPU infrastructure, ensuring deployment readiness and performance across enterprise environments. Responsibilities include model optimization, designing inference pipelines, resolving performance bottlenecks, and conducting applied research on AI systems.

Lead design and development of high-performance backend applications in C/C++; own architecture decisions, optimize performance and memory, mentor engineers, drive best practices, collaborate with cross-functional teams and US-based clients, and ensure reliability via testing and troubleshooting.