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Principal Software Engineer

Company Context

BrightInsight is a leading global regulated digital health platform for biopharma and medtech, delivering pre-built, compliant infrastructure (ISO 13485, HIPAA, GDPR, MDSAP) that accelerates time to market, supports millions of patients, manages over 20 million API calls per day, and scales securely across products, therapy areas, and global markets.

Summary

Principal Software Engineer at BrightInsight, Apr 2020 to Apr 2024. Led cross-functional development of regulated digital health platforms, working at the intersection of software engineering, compliance, and AI across distributed systems, MLOps, and infrastructure automation.

Responsibilities

  • Orchestrated development of global health data platforms spanning AWS, Azure, and GCP, applying modular microservice architecture and secure-by-default practices across Go, JavaScript, and C#
  • On GCP specifically, ran microservices on GKE with service-mesh mTLS, used Cloud Pub/Sub for event-driven flows between regulated workloads, Cloud SQL for transactional data, Cloud Storage for artefacts and audit evidence, BigQuery for analytics across global cohorts, and Cloud KMS for envelope encryption and key custody aligned with HIPAA and ISO 13485 controls
  • Designed a unified Gherkin-based DSL for QA, enabling traceable test artefacts across unit, contract (Pact), and BDD layers — directly mapped to ISO 13485 and IEC 62304 audit requirements
  • Pioneered a compliance-driven continuous delivery workflow for indemnity insurance: decoupled decision-making rules and questionnaire answers from application code, transforming them into a JSON-based data structure that evolved into a domain-specific language (DSL)
  • Partnered with underwriters to shape a JSON DSL that captured indemnity logic as data, so underwriters owned product evolution end-to-end — engineering joined only to extend DSL primitives, not to ship rule changes
  • Ensured legal compliance by retesting every previously answered questionnaire within a defined time window, guaranteeing deterministic results (same inputs → same outputs) while maintaining daily production releases
  • Created CI/CD pipelines with embedded DevSecOps gates, using GitHub Actions, Terraform, and Ansible to enforce infra compliance pre-deployment
  • Integrated early-stage LLMs to build predictive models for patient deterioration, leading to 25% improved detection rates and supporting clinical decision-making workflows
  • Embedded contract testing and consumer-driven development across 8 global teams, standardising delivery with shared test harnesses and documentation-as-code
  • Championed the use of self-describing APIs and composable platform modules, significantly reducing onboarding friction and enabling parallel team autonomy
  • Contributed code daily across stacks, and mentored engineers on regulated delivery, ML-integration pipelines, and cloud-native design

Outcomes

  • Improved patient deterioration detection rates by 25% by integrating early-stage LLM-driven predictive modelling into clinical workflows.
  • Standardised delivery across 8 global teams through embedded contract testing and consumer-driven development.
  • Managed platform handling over 20 million API calls per day at scale.
  • Strengthened audit readiness by mapping test evidence directly to ISO 13485 and IEC 62304 requirements via a shared Gherkin-based DSL and delivery gates.
  • Pioneered a data-driven decision model for indemnity insurance that enabled daily production releases while maintaining legally mandated deterministic compliance — same inputs always produce the same results within the required time window.
  • Empowered underwriters to independently create, modify, and test insurance products via a JSON-based DSL, eliminating engineering bottlenecks and fostering cross-disciplinary collaboration.

Reusable CV Bullets

  • Orchestrated development of global health data platforms spanning AWS, Azure, and GCP, applying modular microservice architecture and secure-by-default practices across Go, JavaScript, and C#
  • On GCP, ran microservices on GKE with mTLS service mesh, Cloud Pub/Sub for event-driven flows, Cloud SQL for transactional data, Cloud Storage for artefacts, BigQuery for cohort analytics, and Cloud KMS for envelope encryption aligned with HIPAA and ISO 13485
  • Designed a unified Gherkin-based DSL for QA, enabling traceable test artefacts across unit, contract (Pact), and BDD layers mapped to ISO 13485 and IEC 62304 audit requirements
  • Pioneered a compliance-driven continuous delivery workflow for indemnity insurance, decoupling decision rules from application code into a JSON-based DSL enabling daily releases while guaranteeing legal determinism
  • Enabled underwriters to independently create, modify, and test insurance products without code changes, fostering cross-disciplinary collaboration and eliminating engineering bottlenecks
  • Created CI/CD pipelines with embedded DevSecOps gates, using GitHub Actions, Terraform, and Ansible to enforce infra compliance pre-deployment
  • Integrated early-stage LLMs to build predictive models for patient deterioration, leading to 25% improved detection rates
  • Embedded contract testing and consumer-driven development across 8 global teams, standardising delivery with shared test harnesses and documentation-as-code
  • Championed self-describing APIs and composable platform modules, reducing onboarding friction and enabling parallel team autonomy
  • Mentored engineers on regulated delivery, ML-integration pipelines, and cloud-native design

Evidence / Source Notes

  • Source: config/madu_profile.json → work_experience[]; reconciled with JobVia export (madu_alikor_export.json).
  • Confidence: high