What the engineers we've placed have delivered

The Situation

A Series B e-commerce SaaS was spending 5 days on manual regression testing every release cycle. Deployments were blocked, feature launches were delayed, and an upcoming enterprise demo was at risk. They needed a senior QA engineer who had built production automation from scratch before — not someone learning Playwright on their codebase.

What the placed engineer delivered

Here is what the placed engineer built in the first 60 days:

• Built a comprehensive end-to-end test suite covering the checkout flow, cart management, and payment integrations
• Integrated the full suite into CI/CD — runs on every commit with no manual trigger
• Set up parallel test execution, cutting suite run time from 4 hours to under 20 minutes
• Added visual regression testing for critical UI components
• Created a shared test data factory to eliminate flaky tests caused by state pollution
• Wrote runbooks and onboarding docs so the internal team could own the suite going forward

The Situation

A Series A fintech startup had a payment processing API timing out at 12+ seconds during peak load. Transaction failures were climbing and the user experience was breaking. The core problem was years of unoptimized queries — N+1 patterns across multiple endpoints, no caching layer, no connection pooling. They needed a senior engineer who had solved this class of problem before, not one who would diagnose it over months.

What the placed engineer delivered

Here is what the placed engineer resolved over the engagement:

• Profiled the full payment processing flow and identified the highest-impact query bottlenecks
• Resolved N+1 query patterns across 14 critical API endpoints
• Built a Redis caching layer for frequently accessed data, cutting repeat DB reads by 80%
• Refactored critical endpoints with connection pooling to handle traffic spikes without degradation
• Added request batching to reduce database round-trips on bulk operations
• Instrumented the stack with New Relic for continuous latency visibility and alerting going forward

The Situation

A multi-region Series A SaaS was spending $65k/month on cloud infrastructure that had never been properly right-sized. Instances were oversized, autoscaling was static, and costs were climbing with no clear ceiling. They did not need an infrastructure manager — they needed a senior DevOps engineer who had done this audit before and could move fast.

What the placed engineer delivered

Here is what the placed engineer delivered over the engagement:

• Conducted a full infrastructure audit across all AWS regions, mapping actual vs. provisioned utilization
• Right-sized 23 oversized EC2 instances based on real traffic data — the largest single source of savings
• Implemented autoscaling policies tied to actual load patterns, replacing static over-provisioning
• Containerized services with Docker and migrated to ECS for consistent, reproducible deployments
• Moved eligible batch workloads to spot instances with on-demand fallback pools
• Rebuilt the CI/CD pipeline — reduced deployment time from 45 minutes to 8 minutes