Staff+ Engineer • Platform Architect • Systems Builder

I design and operate SaaS systems in regulated environments (legal tech, audit-heavy workflows) that scale under growth, audits, outages, and real business pressure.

• Designed distributed platforms processing millions of daily events across production services
• Increased deployment frequency from monthly releases to daily delivery
• Reduced cloud spend through architecture redesign and workload optimization
• Introduced organization-wide observability and reliability practices
• Turned ambiguous product initiatives into shipped, maintainable systems

I work at the intersection of engineering execution, architecture, and business outcomes.

• Architect distributed backend and data platforms
• Translate product ambiguity into pragmatic technical direction
• Build reliable cloud infrastructure and internal platforms
• Reduce operational risk through automation and observability
• Coach engineers toward senior and staff-level impact

I optimize for long-term delivery speed, not short-term heroics.

• API platform design
• Event-driven architectures
• High-concurrency services
• Performance and scalability engineering
• Distributed transactions and failure handling

• Streaming and batch data pipelines
• Data reliability engineering
• Warehousing and analytics foundations
• Internal developer platforms

• AWS architecture and cost optimization
• Infrastructure as Code
• Production readiness and incident response
• SLO-driven reliability engineering

Languages Kotlin • Python • Java • SQL

Data Systems Kafka • PostgreSQL • Airflow • dbt • Spark • Snowflake

Infrastructure AWS • Terraform • Docker

Observability OpenTelemetry • Prometheus • Grafana

• Reliability over novelty
• Simple systems scale better than clever ones
• Measure before optimizing
• Automating repetitive work compounds engineering output
• Architecture exists to enable product velocity

Examples of problems I enjoy solving:

• High-throughput event ingestion and processing platforms
• Developer platforms improving team delivery speed
• Organization-wide observability adoption
• Cost-efficient cloud architectures at scale
• Data-intensive backend systems

• Platform engineering
• Data-intensive applications
• Event-driven systems
• Observability and reliability engineering
• AI-assisted engineering workflows

Interested in:

• Early-stage or scaling technical leadership
• Architecture reviews and technical due diligence
• Platform and infrastructure strategy
• Hard production problems

• LinkedIn → https://linkedin.com/in/mfilenko
• Email → hello@filenko.ms