Job Description

Akila is looking for a Senior DevOps Engineer with ambition, creativity and a passion for sustainability and technology. Our team is involved in a wide variety of technologies, like digital twin, 3D engine development and cross platform development. This role will be critical for Akila’s development, as it represents both Mobile and Web platform. Candidate should be comfortable working in a fast-moving startup environment where speed, hard work and fresh thinking are critical to success.

Key Duties and Responsibilities:

In charge of automated operations, deployment, monitoring, service governance, and optimization of the Akila platform.
Ensure reliable project delivery across on-prem and cloud environments.
Analyze and troubleshoot issues, with the ability to respond quickly to incidents and emergencies.
Collaborate with development teams for daily support and system improvements.

Core Skill Areas (Candidate only needs to be strong in ONE of the following)

1. NVIDIA Stack & On-Prem Deployment

Experience working with the NVIDIA ecosystem (e.g., GPU Operator, Nvidia Blueprints, Omniverse).
Strong knowledge of on-premise infrastructure deployment and operations.
Familiar with GPU-based and streaming workloads (AI/ML systems, inference/training environments).
Experience in system optimization and performance tuning for GPU workloads.

2. DevOps & Application Operations

Experience with DevOps tools and technologies: Git, Jenkins, Terraform, Docker, Kubernetes, ELK, Prometheus.
Experience setting up and operating cloud environments (preferably Azure).
Familiar with PaaS services such as MySQL, Redis, ClickHouse, IoT Time Series DB, CDN, etc.
Proficient in Linux system administration and command-line tools.
Experience maintaining application services and security in production environments.
Ability to perform zero-downtime upgrades for critical systems and services with strict SLAs.

3. Cloud Autonomous Agents & AI Platform

Experience with AI/Agent systems, including:

Environment setup and infrastructure for agent-based systems.
Agent development workflows and lifecycle management.
Integration of coding agents into development pipelines.

Understanding of modern AI platform architecture, including:

MCP (Model Context Protocol) or similar context-sharing mechanisms.
Agent skills/modules design and orchestration.
Multi-agent systems and tool integration.
Secure sandbox environments for agent execution (code execution isolation, resource limits, security controls).

Ability to design and operate scalable, production-ready AI agent environments.

General Requirements