ChargeSmart Insight
EV charging analytics that makes smarter placement decisions
£10K
Monthly recurring revenue
Reached in under 6 months
70%
Cloud cost reduction
$700 → $100/month
100M+
Daily records
From 30+ APIs via event-driven pipelines
−90%
Incident detection
Via internal observability platform
About this role
ChargeSmart Insight helps EV companies make smarter decisions about where to place charging stations, a problem that directly impacts EV adoption. I joined two non-technical partners as the sole technical owner in a fractional role: I defined the full architecture, selected the stack, and led all engineering decisions to reach £10K MRR in under 6 months, in a squad of 4, with zero external funding.
I redesigned the system architecture from EC2/PostgreSQL to a serverless AWS stack, weighing cold-start tradeoffs before committing to Lambda and Aurora, and reducing cloud spend by 70% ($700 to $100/month). I built an event-driven architecture on SQS and AWS Batch with idempotent consumers that ingests over 100 million records per day from 30+ APIs, cutting processing time from hours to minutes.
I also set up CI/CD with GitHub Actions covering automated testing, linting, and zero-downtime deployments across all environments, and built an internal observability platform monitoring 70+ pipelines across 7 countries, reducing incident detection time by 90%. The codebase is fully country-agnostic, enabling multi-market expansion without engineering overhead.
Tech stack
Company website
Key achievements
£10K MRR in under 6 months
Led the product from scratch to £10K MRR in a squad of 4, owning React frontend, Python API, and AWS infrastructure — as the sole technical owner alongside two non-technical partners, with zero external funding.
70% reduction in cloud costs
Moved from EC2 and PostgreSQL to serverless with Lambda and Aurora, weighing cold-start tradeoffs before committing, cutting AWS spend from $700 to $100/month.
100M+ records ingested daily from 30+ APIs
Designed Python ingestion pipelines on SQS and AWS Batch with idempotent consumers, unifying 30+ APIs at over 100 million records per day, cutting processing time from hours to minutes.
90% faster incident detection
Built an internal observability platform monitoring 70+ pipelines across 7 countries, with automated Slack alerts replacing hours-long manual checks.
Zero-downtime CI/CD
Set up GitHub Actions covering automated testing, linting, and zero-downtime deployments across all environments.