Hands-on implementation
Applications, APIs, integrations, reporting, automation, data movement, and complex backend engineering.
About bobparsons.dev
Practical technology work, owned from idea through support.
I help teams build and improve consequential software. The work ranges from hands-on coding, reporting, performance, and reliability to consultation, engineering standards, organizational leadership, and practical AI adoption.
The standard for the work
- UsefulBuilt around a real workflow and a measurable outcome.
- UnderstandableTradeoffs, risks, and decisions explained plainly.
- SupportableDesigned for the people who will use and own it.
How I help
One delivery path from exploration to steady operation
Engagements can begin with a delivery problem, a performance bottleneck, a reporting need, an architecture decision, or a team that needs senior technical guidance.
Performance and reliability
Profiling, batching, indexing, messaging recovery, observability, and standards that improve production systems.
Consultation and enablement
Architecture guidance, engineering leadership, team standards, AI adoption, training, and ongoing support.
Working principles
Clear thinking before extra technology
Good delivery depends on choosing the right problem, making tradeoffs visible, and leaving behind something the team can operate.
Pragmatic
Use the simplest approach that solves the actual problem, whether the answer is code, reporting, standards, process, or AI.
Collaborative
Work closely with the people who understand the process and will use the result every day.
Accountable
Own the implementation details, communicate directly, and stay engaged when production reveals what needs improvement.
Technical range
Technical depth across complex systems
Useful engineering work connects architecture, implementation, operational context, business reporting, and the standards that help teams make safer changes.
Applications, data, and reporting
Web applications, APIs, internal tools, complex reporting, imports, migrations, and business-aligned insights.
Knowledge and observability
Nexus dependency graphs, blast-radius awareness, domain-specific metrics, team-owned alerts, and system context.
Reliability and performance
Performance optimization, maintainability, event-driven recovery, engineering standards, and operational support.
HealthJoy | Engineering leadership
Engineering judgment shaped by hands-on and organizational responsibility
Recent experience spans hands-on architecture and implementation through manager-of-managers leadership and nine months representing Engineering directly to the CEO.
Manager of managers
Led an organization with a peak of 14 engineers and 2 managers while continuing to drive architecture and technical maturity.
Standards across 70 services
Authored and enforced standards for batching, validation, indexing, and safer engineering practices across a large service estate.
Sustained performance
Increased net productivity by 15% through prioritization and process discipline despite a 30% reduction in staffing.
Selected delivery work
Improvements measured in the workflow, not the demo.
These projects started with operational friction and ended with software designed to keep working as the business grew.
Case study
Critical-service performance and cloud cost
A critical eligibility service took three hours to process work, required 20 pods, and placed unnecessary pressure on database infrastructure.
- 97% faster processing: 3 hours to 4 minutes
- 75% reduction in pod requirements: 20 to 5
- 20% immediate reduction in RDS cloud spend
What changed
The workflow was refactored around batching, indexing, and targeted performance optimization. The result improved customer-facing throughput while materially reducing infrastructure requirements.
Case study
Nexus knowledge infrastructure
Engineers working across a complex service estate lacked a reliable way to understand dependencies, event relationships, database coupling, and the likely blast radius of a change.
- Engineer ramp-up reduced from 1 month to 1 week
- Blast-radius awareness added to ticket planning
- Real-time producer, consumer, and cross-domain dependency context
What changed
Nexus was architected as a real-time service dependency graph that ingested repository changes and translated distributed-system relationships into usable engineering context.
Case study
Business-aligned reporting and observability
Surface-level technical metrics did not explain whether critical business workflows were healthy or give teams enough context to respond quickly.
- Eligibility throughput and queue depth made visible
- Error reporting aligned to business workflows
- Team-owned alerts surfaced actionable context immediately
What changed
Domain-specific reporting replaced generic dashboards with metrics tied to business behavior. The same approach supports complex client reporting where data must be joined, interpreted, and made useful.
Case study
Engineering standards and messaging reliability
A 70-service estate had inconsistent performance practices and a high-risk RabbitMQ architecture with silent-failure risks in critical business flows.
- Standards established for batching, validation, and indexing
- Automated pre-MR review reduced architectural drift
- ACK patterns, dead-letter queues, and replay capability added
What changed
General engineering standards were authored and enforced while fragile event-driven workflows were remediated with explicit failure handling and recovery paths.
Have a problem worth solving?