Career Dashboard
Current Target Role: Cloud / DevOps Engineer (primary); Platform / MLOps Engineer (secondary)
Original Time-to-Hire Estimate: 3–6 months
Current Time-to-Hire Estimate: 2–4 months
Confidence Level: Medium
Skills Acquired: Portfolio repo with IaC, CI pipeline, containerized service, basic monitoring; screening call prep.
Remaining Skill Gaps: Managed Kubernetes deployment, deeper cloud networking, security hardening, live interview practice.
Today’s Objective
Convert the portfolio into job opportunities by applying to roles, reaching out to recruiters, and beginning screening conversations. The goal was to test the market and gather feedback that will inform the next iteration of the plan.
What I Worked On
I tailored my resume to highlight operational impact and the portfolio project, wrote concise cover letters for each role, and submitted applications to a mix of Cloud/DevOps and Platform/MLOps positions. I reached out to recruiters on LinkedIn with a short message and a link to the portfolio. Two recruiters responded and scheduled screening calls.
What I Learned
Recruiters respond to clarity and evidence. A short message that includes a one‑line summary of what I built, a link to the repo, and my availability gets more responses than a generic “I’m looking” note. Recruiters also asked for availability and salary expectations early, so I prepared a realistic compensation range based on market signals and my experience. A few recruiters asked whether I had any AI experience; I replied honestly and offered to add a short RAG demo to the repo if they wanted to see AI‑adjacent work.
Market Observations
Early recruiter feedback confirmed the earlier assessment: hiring teams want demonstrable IaC and CI/CD experience, plus the ability to explain incident response. Some teams are also asking for basic scripting (Python/Bash) and familiarity with managed Kubernetes. This validates the plan to prioritize Kubernetes next.
Resources Reviewed
I reviewed screening call guides and common DevOps interview questions to prepare. These helped structure answers and reduce interview anxiety. I also reviewed a few salary band references to set realistic expectations for recruiter conversations.
Progress Against Plan
Ahead. Portfolio is live, applications are submitted, and recruiter conversations are scheduled. This early momentum shortens the expected time‑to‑hire if interviews go well.
Strategy Changes
No major pivots. I will add a short AI‑adjacent demo to the portfolio only if recruiter feedback indicates it will materially improve interview outcomes. I will prioritize managed Kubernetes labs next.
Next Steps
Prepare for screening calls with STAR stories drawn from the portfolio and past production incidents. Continue Kubernetes labs and add a managed cluster deployment. Track applications, interviews, and feedback in a simple spreadsheet and iterate the portfolio based on recruiter input.
Reflection
The first ten days have been about converting experience into evidence and testing the market. The combination of a focused portfolio, clear documentation, and targeted outreach is producing recruiter interest. The work ahead is to deepen Kubernetes and cloud skills and to convert screening calls into technical interviews. I’ll continue to document rejections, feedback, and time spent so the plan can be continuously improved.
