JobsFlow

Why your resume keeps getting rejected.

If you're sending a lot of applications and hearing very little back, it usually isn't your experience. It's that the resume doesn't use the posting's language, so it never gets to the person who would recognise it.

Four reasons, in the order they usually bite.

The posting's words aren't on the page

Recruiters search their applicant tracking system for the terms in the job description. If the posting says "infrastructure as code" and your resume says "deployment scripts", you don't come up.

One resume for every role

A resume written for every job reads like it was written for none. The relevant work is there, buried under the rest.

Two pages of everything

Reviewers skim. A second page mostly dilutes the lines that matter for this role.

The role was never a fit

No rewrite fixes a role that needs five years you don't have, or a visa the company won't sponsor. Picking better roles does more than polishing one resume.

What JobsFlow changes.

One master resume in. A posting-specific, one-page PDF out, with a check you can read.

  1. Pulls the keywords from the posting

    The skills, tools and phrases the job description actually uses, one list per role.

  2. Rewrites three sections around them

    Skills, Experience and Projects are reworded and reordered so the relevant work leads. Your employers, titles and dates aren't touched.

  3. Checks the result in code

    At least 75% of the posting's keywords on the page, matched as whole words, so "Java" never counts for "JavaScript". One page. No employer dropped. If the check fails, it tries again with the failures spelled out.

The resume check in JobsFlow: a score of 82, matched and missing keywords, and a one-page result
The check as it appears in the app. Gaps you can't claim are listed, and excluded from the score.

A tailored resume, up close.

The PDF JobsFlow generates for a fictional platform engineer, and the check the app shows for it.

Sample · fictional candidateGenerated resume for Platform Engineer, Ledgerline
Maya Kapoor

maya.kapoor@example.com | linkedin.com/in/example | github.com/example | Bengaluru, India

Skills

Infrastructure: Kubernetes (EKS), Terraform, AWS (EC2, RDS, IAM, VPC), Docker, Argo CD
Languages: Go, Python, SQL, Bash
Delivery and reliability: CI/CD with GitHub Actions, Prometheus, Grafana, OpenTelemetry, on-call, incident response, SLOs
Data: Postgres, Redis, Kafka

Experience

Platform Engineer, Infrawise, Bengaluru | Mar 2022 – Present

  • Run 40 services on Kubernetes (EKS) across two AWS regions for a 60-person engineering team; moved the last 12 services off EC2 with no customer-facing downtime.
  • Rebuilt all deployments as Terraform modules across three AWS accounts, replacing hand-written scripts and cutting new-environment setup from two days to under an hour.
  • Set up Prometheus, Grafana and OpenTelemetry, and the SLO dashboards product teams now use to debug their own services.
  • Share the platform on-call rotation and take part in incident response, writing postmortems and tracking their follow-up actions to closure.
  • Built a Go CLI that creates a preview environment for every pull request, now used by 9 teams.
  • Moved CI/CD from Jenkins to GitHub Actions and Argo CD, taking the median deploy from 25 minutes to 6.
  • Wrote the Kubernetes upgrade runbook and ran four EKS version upgrades without a failed rollout.
  • Added per-team AWS cost alerts, which flagged idle RDS instances worth $4,000 a month that were then removed.
  • Standardised service templates with health checks, Prometheus metrics and Terraform-managed IAM roles, so a new service ships with them by default.
  • Mentor two junior engineers and run fortnightly platform office hours for product teams.

Backend Engineer, Corvid Labs, Pune | Jul 2019 – Feb 2022

  • Wrote the billing service in Go on Postgres, handling payouts for 3,000 merchants.
  • Partitioned the largest Postgres tables and added read replicas, taking p95 report queries from 9s to 800ms.
  • Moved the test suite into a CI/CD pipeline on GitHub Actions, cutting release time from a day to an hour.
  • Added structured logging and Prometheus alerts on the payments path, which caught two failed-payout incidents before merchants reported them.
  • Containerised the four core services with Docker ahead of the company's move to Kubernetes.
  • Designed idempotent retries for the payouts queue on Redis, which ended duplicate payouts.
  • Moved the main database from a self-managed Postgres instance to AWS RDS with point-in-time recovery.
  • Shared the backend on-call rotation and wrote the first incident response checklist for the payments team.

Software Engineer, Tessellate Systems, Bengaluru | Jun 2018 – Jun 2019

  • Built internal REST APIs in Python and Postgres for the operations team's order tooling, used daily by 40 staff.
  • Joined the support on-call rotation and fixed the order-sync bug behind most weekend incidents.
  • Wrote the runbooks for the support rotation, documenting the five most common fixes and cutting repeat tickets.
  • Automated nightly database backups and restore checks with Bash and cron.
  • Wrote a Python job that reconciled orders against the payment provider each night and flagged mismatches.
Projects

kube-cost-report | Open source, 600 GitHub stars

  • Go CLI that breaks a Kubernetes bill down by team and namespace from AWS cost and usage reports.

terraform-aws-baseline | Internal, Infrawise

  • Reusable Terraform modules for VPC, IAM and RDS defaults, used across every Infrawise AWS account.

pg-migrate-check | Open source

  • Go linter that flags Postgres migrations likely to lock large tables, run in CI/CD before merge. Adopted by two other startups.
Education

B.Tech, Computer Science | 2014 – 2018
Final-year project: a distributed log collector written in Go.

Certifications

Certified Kubernetes Administrator (CKA), 2023 | HashiCorp Certified: Terraform Associate, 2022
AWS Certified SysOps Administrator – Associate, 2021

See a tracker and outreach drafts too →

Questions about tailoring.

Does an ATS automatically reject my resume?

Usually not on its own. Most applicant tracking systems store applications and let recruiters search and filter them. The problem is quieter: if the words a recruiter searches for aren't on your resume, you don't come up, and a human never reads it.

Isn't tailoring just keyword stuffing?

Not the way JobsFlow does it. It only uses keywords your master resume can back up. Anything you can't claim is listed as a gap, and it doesn't count against the score.

Will it change my job titles or dates?

No. Names, employers, titles and dates stay exactly as they are on your master resume. Only the wording of your Skills, Experience and Projects sections changes.

What does one tailored resume cost?

Tailoring is on the paid plans: 10 a month on Pro ($19) and 30 on Power ($39). Re-running one you already generated doesn't use another.

Which format does it produce?

A one-page PDF from your own master resume, A4 by default, the standard size in India and Europe.

Send fewer resumes, and better ones.

Start free with search and fit scores. Tailoring is on Pro and Power.

Start freeSee pricing