Overview

TekWissen is a global workforce management provider throughout India and many other countries in the world. The below job opportunity is to one of our clients who is a part of a trusted global innovator of IT and business services headquartered in Tokyo. We help clients transform through consulting, industry solutions, business process services, IT modernization and managed services.

This client enables us to move confidently into the digital future. This client committed to Long Term success and combine global reach with local client attention to serve them in over 50 Countries.

Position: Systems Integration Senior Specialist

Location: Bangalore/Hyderabad

Work Type: Hybrid

Job Type: Full Time

- Senior AI Platform &
- GPU-as-a-Service (GPUaaS) Engineer The Senior AI Platform &
- GPU-as-a-Service (GPUaaS) Engineer is responsible for building, operating, automating, and optimizing the enterprise AI Platform &
- Acceleration Services (AIPAS) capability supporting Artificial Intelligence (AI), Generative AI (GenAI), Machine Learning (ML), Large Language Models (LLMs), High Performance Computing (HPC), and GPU-enabled workloads.

- This role will partner with architecture, infrastructure, security, networking, storage, OpenShift Engineering, and Line of Business teams to deliver a production-ready GPU platform that enables scalable and secure AI adoption across the enterprise.

- The engineer will support functions ranging from platform engineering, customer onboarding, GPU workload enablement, operational readiness, observability, capacity management, automation, self-service capabilities, and service optimization.

- The role requires a combination of platform engineering expertise, operational experience, automation skills, and customer engagement capabilities.

- The ideal candidate is comfortable operating across infrastructure, platforms, AI workloads, automation, and operations while helping transform GPU infrastructure into an enterprise GPU-as-a-Service offering.

Education

Job Requirements

- Bachelor's degree in Computer Science, Engineering, Information Technology, or related discipline (or equivalent experience).

Experience Required

- 5 years of Platform Engineering, Infrastructure Engineering, Cloud Engineering, Site Reliability Engineering (SRE),



or related experience 3 years of Kubernetes and/or OpenShift experience

- Experience operating and supporting enterprise production platforms

- Experience automating infrastructure and platform services

- Experience supporting highly available and distributed systems

- Familiarity with Machine Learning Familiarity with Large Language Models in both Inferencing and Fine Tuning scenarios

- Experience working across multiple technology teams, including infrastructure, security, application, and operations teams

- Experience with NVIDIA GPU infrastructure Preferred 7 years of enterprise engineering experience

- Experience with OpenShift AI platforms Experience with Python, CUDA and Golang

- Experience in highly regulated enterprise environments (Financial Services preferred)

- Experience implementing self-service platform capabilities

- Experience building operational and executive reporting solutions

Core Competencies

- Strong troubleshooting and analytical skills Customer-focused mindset

- Strong verbal and written communication skills

- Ability to translate business requirements into technical solutions

- Ability to work independently and lead technical initiatives Solid collaboration and stakeholder management skills

- Automation-first mindset Continuous improvement and operational excellence focus

Skill Set

Must-Have Skills

- Platform Engineering Red Hat OpenShift (OCP) administration

- Kubernetes administration and operations

- Linux administration Enterprise compute, storage, and networking Container platform management(desired)

- Production platform operations

- Automation &
- DevOps

- Ansible Terraform(desired)

- Infrastructure-as-Code (IaC) Git/GitHub CI/CD pipelines

- Python and/or Bash scripting

- Operations &

- Reliability

- Production support(understanding banks regulatory env )

- Monitoring and alerting Incident, Problem, and Change Management Root Cause Analysis (RCA)





- Disaster Recovery concepts Runbook development Observability &

- Capacity Management Prometheus Grafana Splunk or equivalent monitoring platforms

- Capacity planning and forecasting Utilization reporting

- Dashboard development SLA/SLO reporting Security &

- Governance RBAC and IAM Kubernetes/OpenShift security Secrets management

- Vulnerability management Security and compliance controls

- Enterprise governance processes Customer Enablement Customer onboarding(desired)

- Technical discovery and requirements gathering(desired)

- Technical documentation(required Cross-functional collaboration(desired)

- Customer-facing engineering support(desired)

Should-Have Skills

- AI &
- GPU Platforms OpenShift AI NVIDIA GPU technologies GPU workload onboarding AI/ML platform operations LLM and GenAI environments(Desired)

- Model training and inference platforms GPU sizing and capacity planning Advanced Automation GitOps (ArgoCD)

- API integration Workflow automation Self-service platform development

- ServiceNow integration(Desired) Enterprise Integration Active Directory integration(desired)

- Enterprise networking Enterprise storage platforms Certificate management(desired)

- GitHub Enterprise ServiceNow(desired)

- Confluence Reporting &

- Analytics Executive dashboards(desired)

- Capacity analytics Consumption reporting Service health reporting

- Operational KPI reporting

Nice-to-Have Skills

- NVIDIA &
- Accelerated Computing Nvidia Enterprise-Class GPU

- Experience NVIDIA AI Enterprise NVIDIA GPU Operator CUDA NCCL TensorRT NVIDIA DCGM HPC &

- Large-Scale GPU Environments NVIDIA SuperPod experience

- HPC platforms Multi-cluster GPU environments Distributed training environments

- GPU fabric technologies AI/ML Engineering MLOps Kubeflow KServe JupyterHub Model registries

- Deep Learning frameworks Platform Optimization GPU performance tuning GPU utilization optimization MIG (Multi-Instance GPU)

- Multi-tenant GPU architectures

- Cost optimization Product &

- Service Management

- Service catalog development Platform product ownership

- Customer experience management Adoption analytics

- Roadmap planning Chargeback/showback models

TekWissen® Group is an equal opportunity employer supporting workforce diversity.

📌 Systems Integration Senior Specialist (Bengaluru)
🏢 Tekwissen India
📍 Bengaluru