English for IT Job Seekers: The Complete Tech Resume & Cover Letter Writing Guide

DO:
- Use plain text or simple-format PDF
- Naturally incorporate keywords from the JD (Job Description)
- Use standard section headings (Experience, Education, Skills)
- Include measurable achievements (numbers!)

DON'T:
- Use complex tables, charts, or images
- Put important information in headers/footers
- Use only abbreviations (ATS may not recognize them)
  -- Write "Kubernetes (K8s)" with full name + abbreviation

Youngju Kim
Seoul, South Korea | youngju@email.com | +82-10-XXXX-XXXX
LinkedIn: linkedin.com/in/youngjukim | GitHub: github.com/fjvbn2003

Bad:
"I am a hardworking software engineer looking for opportunities."

Good:
"Platform Engineer with 4+ years of experience building and scaling
Kubernetes-based AI/ML infrastructure. Led migration of 200+ services
to cloud-native architecture, reducing deployment time by 73%.
Certified Kubernetes Administrator (CKA) with expertise in GitOps,
observability, and GPU workload management."

Bad:
"Was responsible for Kubernetes cluster management."

Good:
"Architected and maintained 15-node Kubernetes cluster serving
50+ microservices, achieving 99.95% uptime and reducing infrastructure
costs by 32% through right-sizing and spot instance optimization."

**Senior Platform Engineer** | Upstage AI | Seoul, Korea
_March 2024 – Present_

• Architected multi-tenant Kubernetes platform serving 30+ ML teams,
processing 500K+ inference requests/day with p99 latency < 200ms
• Designed and implemented GitOps pipeline using ArgoCD and Helm,
reducing deployment frequency from weekly to 15+ deploys/day
• Built GPU scheduling system with NVIDIA GPU Operator and MIG,
improving GPU utilization from 35% to 78% across 40+ A100 nodes
• Developed comprehensive observability stack (Prometheus, Grafana,
Loki, Tempo) reducing MTTR from 45min to 8min
• Mentored team of 5 junior engineers on cloud-native best practices

**Technical Skills**
• Infrastructure: Kubernetes, Docker, Terraform, Ansible, Helm, ArgoCD
• Cloud: AWS (EKS, EC2, S3, Lambda), GCP (GKE)
• Observability: Prometheus, Grafana, Loki, Tempo, OpenTelemetry
• Languages: Python, Go, Bash, TypeScript
• AI/ML: vLLM, TensorRT-LLM, Ray, MLflow, NVIDIA Triton
• Databases: PostgreSQL, Redis, Qdrant, Elasticsearch
• Certifications: CKA, CKS, KCNA, AWS SAA

**B.S. in Computer Science** | Korea University | 2016 – 2020
• GPA: 3.8/4.5 (only include if > 3.5)
• Relevant Coursework: Distributed Systems, Machine Learning, OS

Paragraph 1: Hook + specify the position you're applying for
Paragraph 2: 1-2 most relevant experiences (with concrete results)
Paragraph 3: Why this company (research is essential!)
Paragraph 4: Call to Action

Dear Hiring Manager,

I'm excited to apply for the Senior Platform Engineer position at
[Company]. With 4+ years of experience building Kubernetes-based
AI infrastructure and a track record of improving system reliability
from 99.5% to 99.95% uptime, I'm confident I can contribute
meaningfully to your platform team.

At Upstage AI, I architected a multi-tenant Kubernetes platform that
serves 30+ ML teams with 500K+ daily inference requests. I designed
the GitOps pipeline that increased deployment frequency by 15x and
built the GPU scheduling system that improved utilization from 35%
to 78%. These experiences directly align with your team's mission
to scale AI infrastructure efficiently.

What particularly excites me about [Company] is [specific project/
product/value from research]. Your recent work on [specific thing]
resonates with my passion for [relevant area], and I'd love to
bring my experience in [specific skill] to help advance these efforts.

I'd welcome the opportunity to discuss how my background can
contribute to your team. Thank you for your consideration.

Best regards,
Youngju Kim

• Reduced [metric] by X% through [action]
• Increased [metric] from X to Y by implementing [solution]
• Delivered [project] ahead of schedule, resulting in $XK savings
• Eliminated [problem] that had caused X hours/week of downtime
• Scaled [system] from X to Y users while maintaining Z performance

• Proficient in / Experienced with / Expert in
• Hands-on experience building [systems] at scale
• Deep understanding of [concept] and its practical applications
• Track record of delivering [type] solutions in production environments

"I think I can..." -- "I will..." / "I am confident..."
"I helped with..." -- "I led..." / "I drove..."
"Responsible for..." -- "Owned..." / "Spearheaded..."
"Team player" -- (Demonstrate through specific collaboration examples)
"Detail-oriented" -- (Show through specific quality improvement metrics)

Bad: "Software Engineer at Company"
Good: "Platform Engineer | Kubernetes • AI/ML Infrastructure • GitOps | CKA/CKS"

I build and scale the infrastructure that powers AI.

As a Platform Engineer at Upstage AI, I architect Kubernetes-based
systems that serve 500K+ daily inference requests with 99.95% uptime.
My focus areas include:

Cloud-native infrastructure (Kubernetes, Terraform, ArgoCD)
AI/ML platform engineering (GPU scheduling, model serving)
Observability at scale (Prometheus, Grafana, OpenTelemetry)

Previously, I [brief prior experience]. I hold CKA, CKS, and KCNA
certifications and am working toward Golden Kubestronaut.

Open to connecting with fellow platform engineers and AI infrastructure
builders. Let's chat!