Jobs at Integrant

Develop technical marketing for AI and agentic solutions by translating engineering specifications into buyer-friendly content. Create technical blogs, case studies, architecture diagrams, demos, comparison materials, FAQs, battlecards, and sales enablement resources. Support technical campaigns, webinars, sales calls, and pre-sales discussions. Research enterprise AI use cases, competitors, and industry trends while collecting customer feedback and analyzing content engagement and business outcomes.

Designs and implements end-to-end data and AI solutions, including data warehouses, lakes, lakehouses, pipelines, semantic layers, streaming systems, and agentic applications. Engages clients to gather requirements, create technical proposals, select architectures, optimize performance and costs, and support production systems. Leads hands-on engineering delivery, data governance, quality, orchestration, and cloud implementations while mentoring engineers and advising teams on DataOps, MLOps, and modern analytical architectures.

Engage U.S. prospects through email, LinkedIn, phone, events, and follow-ups; research accounts, conduct discovery, qualify leads, and convert qualified prospects into sales opportunities. Schedule meetings for sales and technical stakeholders, maintain accurate CRM records, collaborate with Marketing on lead quality and messaging, and represent Integrant at client meetings and industry events. Travel approximately five to six times annually.

Engage and qualify U.S. business and technology prospects through email, LinkedIn, phone, events, and follow-ups. Research accounts, conduct discovery conversations, explain technology consulting services, qualify leads, schedule meetings, maintain accurate CRM records, and collaborate with marketing on lead quality and messaging. Represent Integrant at customer meetings and industry events, with approximately five to six trips annually.

Own positioning, content strategy, thought leadership, integrated campaigns, demand generation, and performance measurement for Integrant’s AI, Agentic, and ADLC services. Translate complex technical capabilities into business-focused messaging for U.S. enterprise buyers, collaborate with technical SMEs and sales, execute campaigns across digital and event channels, generate qualified leads, and connect marketing activity to meetings and pipeline outcomes.

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 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 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.

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

Lead end-to-end design, development, deployment, and monitoring of ML and Generative AI solutions (including RAG and agentic AI). Build scalable data pipelines and production MLOps on Databricks/Spark and cloud platforms, conduct research and experimentation, mentor junior team members, engage clients to translate business needs into AI solutions, and ensure model reliability, monitoring, and continuous improvement.

Lead DevOps/SysOps Engineer to deploy, configure, and maintain large-scale Linux/Windows servers and HPC clusters. Manage containerization (Docker, Kubernetes), CI/CD/GitOps, cloud deployments (AWS/Azure/GCP), infrastructure-as-code (Terraform, Ansible), networking (Infiniband, cluster networking), security controls, and monitoring. Automate tasks with Bash and Python, troubleshoot systems and networking, and collaborate with development teams on SDLC and performance tuning.

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.

Responsible for managing data storage infrastructures, including provisioning, configuration, monitoring, and troubleshooting storage environments. Requires extensive experience with Weka and Ceph, and strong Linux administration skills.

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.

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.