Junior DevOps Engineer

We're hiring.

Junior DevOps Engineer Acceler8 AI · Metro Manila, Philippines (Hybrid) · Full-Time

About Acceler8 AI

We are an AI-Driven Media ROI™ company. We accelerate enterprise media for the AI era — through custom AI technology, proprietary licensing platforms, and the operational layer that drives performance.

Culture to commerce. Insight to revenue. Engineering to outcome.

Headquartered in Singapore with operations across Hong Kong, Manila, and Dubai, we work with enterprise brands, indie agencies, and in-house marketing teams across APAC and MENA through three integrated offerings: AI-Powered Paid Media, AI Engineering & Growth Consulting, and AI Platform Licensing.

The Role

We are hiring a Junior DevOps Engineer to own the operational health of our growing AI infrastructure based in Manila.

You will be the hands-on operator for our cloud environments, deployments, monitoring, and incident response across our website, CRM, automation workflows, and proprietary AI platforms. This role sits at the center of how Acceler8 AI keeps production running and how we scale our infrastructure as the business grows.

This is a development-track role designed as a launchpad, not a terminal position. We are looking for someone with 1 to 3 years of DevOps, cloud, or infrastructure experience — hungry, ambitious, AI-native, and ready to grow into a senior infrastructure operator over 18 to 24 months.

You will work directly with senior engineering leadership and have visibility into strategic technical decisions from day one. You will not be architecting from scratch in month one - but you will progressively take on more ownership of the operating layer as you ramp.

You're a strong fit if you have...

• A degree, bootcamp, or self-directed equivalent in Computer Science, Computer Engineering, Information Technology, or a related technical discipline — we assess what you've shipped over where you studied
• 1–3 years of professional, internship, or freelance experience in DevOps, cloud engineering, site reliability, platform engineering, or technical operations
• Working fluency with at least one major cloud platform — AWS, GCP, or Azure — through coursework, certification, or production experience
• Container fundamentals — Docker basics, container deployment, ideally some Kubernetes exposure
• CI/CD experience — GitHub Actions, GitLab CI, CircleCI, or comparable pipelines for deployment automation
• Infrastructure-as-code awareness — Terraform, Pulumi, AWS CDK, or comparable; production experience not required, but you've seen the patterns
• Monitoring and observability — Datadog, Grafana, New Relic, CloudWatch, or similar; basic dashboard creation and alert configuration
• Scripting proficiency — Bash, Python, or Node.js sufficient to automate routine operations and read existing automation code
• Git fluency — branch management, pull request workflow, deployment coordination
• Working with AI development tools — Cursor, Claude Code, GitHub Copilot, or comparable AI-native engineering environments
• Excellent written English — you will be communicating across Slack, GitHub issues, runbooks, and post-incident reports continuously
• Strong organizational instincts, attention to detail, and follow-through
• Velocity — you can pick up a new tool, service, or framework over a weekend and ship something with it by Monday

Bonus points if you have already...

• Shipped something real — a deployed personal project, contributed to open source, run a Discord bot in production, automated a workflow that other people use
• Worked with HubSpot, Make.com, n8n, or other no-code/low-code automation platforms at production scale
• Used LLM APIs and agentic patterns — OpenAI, Anthropic, Google — including prompt engineering and tool use
• Experience with PostgreSQL, Redis, or similar databases at the operations level
• Familiarity with server-side analytics — GA4, GTM server-side, Looker Studio, BigQuery
• Worked with serverless platforms — AWS Lambda, Vercel, Cloudflare Workers, Supabase
• Run incident response for production systems — even small ones
• Built personal dashboards or monitoring for your own projects
• An active GitHub presence with a portfolio of side projects
• Contributed to or built AI-native developer tooling

We care less about where you studied and more about what you've shipped, what you read, and what you've taught yourself in the past 12 months. If you don't meet every line — apply anyway. Demonstrated drive and learning velocity outweigh the resume here.

Soft skills we look for

Ownership mindset · operational discipline · proactive communication · written clarity · service orientation · intellectual curiosity · comfort with ambiguity · discretion and judgment (you will have access to production systems and sensitive credentials) · pace and follow-through · coachability · calm under incident pressure.

What you'll do (and learn)

• Monitor production systems across our website, CRM, automation workflows, and proprietary platforms — uptime, performance, error rates, integration health
• Manage deployments for site updates, workflow changes, and platform releases
• Build and maintain runbooks documenting how every system runs, fails, and recovers — your work outlasts your tenure
• Respond to incidents — alerts, outages, integration failures — with structured escalation when needed
• Automate operational toil progressively — anything you do twice manually gets a script the third time
• Manage credentials and access across our SaaS stack and cloud environments with proper hygiene
• Build internal dashboards for system health, cost monitoring, and operational performance
• Support our AI infrastructure — LLM API integrations, vector databases, agentic systems running in production
• Document everything in our shared knowledge base — workflows, runbooks, post-incident reports, architecture decisions

Your first 90 days

• Day 30 — Foundations: Onboarded across all systems (website infrastructure, CRM stack, automation workflows, cloud environments, monitoring tools). Production access provisioned with proper security hygiene. First three runbooks documented and reviewed. Familiar with all production workflows.
• Day 60 — Activation: Independently handling routine deployments and monitoring duties. First incident response handled under mentorship. Two automation scripts written for recurring operational tasks.
• Day 90 — Contribution: Owning daily operational health independently. First independently-owned automation project delivered (monitoring dashboard, deployment improvement, or cost optimization). Cleared the Day 90 review with strong signal toward expanded scope in Months 4–6.

Compensation and engagement

• Monthly salary calibrated to experience and demonstrated technical instinct
• Performance-linked bonus tied to uptime, incident response, and operational milestones
• Structured learning budget for cloud certifications, courses, and conferences
• Equity participation pathway for high performers
• 13th month, HMO with dependent coverage, SSS / PhilHealth / Pag-IBIG, paid leave
• Hybrid working — Metro Manila base, with regional collaboration across Singapore, Hong Kong, and Dubai
• Clear progression: Junior DevOps → DevOps Engineer → Senior DevOps Engineer, supported by a defined promotion track and visible benchmarks

Why this is the role to take

• You will be a dedicated infrastructure operator at a venture-stage AI company — high visibility, real ownership, direct mentorship from senior engineering leadership
• You will gain visibility into the full operational lifecycle of AI-native marketing infrastructure — from website and CRM through to proprietary AI platforms running in production
• You will operate AI-native by default — Cursor, Claude Code, AI-assisted incident response, automated runbook generation
• You will benefit from regional exposure across Singapore, Hong Kong, Manila, and Dubai from day one
• You will join early enough for your contribution to be visible in the company's technical playbook, compensation structure, and equity story.

How to apply

Send the following to [email protected]:

• CV (PDF preferred)
• Links to projects, GitHub profile, or portfolio
• A short cover note (max 300 words) answering one of the following — your choice:

1. The most interesting infrastructure or DevOps problem you've solved in the past 12 months, and how you approached it.
2. A development in cloud infrastructure, observability, or AI-native operations over the past 12 months that has shaped how you think about technical operations, and why.

Applications reviewed on a rolling basis. Shortlisted candidates receive an asynchronous technical assessment within five working days. Final candidates complete a brief paid trial project before any offer is extended.

Acceler8 AI is committed to building a team that reflects the diversity of the markets we serve. We evaluate every candidate on merit, skill, and fit.