Bio

Bio

I’m a senior backend engineer with 5+ years of experience specializing in Go and cloud-native systems.

I design, build, and operate production systems with a strong focus on reliability, performance, and clear system boundaries. I work close to real infrastructure — Kubernetes, CI/CD, observability, incident response, and platform configuration — and care deeply about making systems understandable and predictable.

I also integrate AI-driven components into backend systems where they add real, measurable value.

What I work on

  • Designing and operating Go-based backend systems in production
  • Building microservices and APIs with clear boundaries and predictable behavior
  • Cloud-native systems using Kubernetes, Docker, Helm, GCP, Azure, and CI/CD pipelines
  • Owning platform configuration through GitOps, Helm charts, and governed configuration repositories
  • Observability-first engineering: metrics, structured logs, and tracing
  • Integrating AI components (LLMs, RAG, agents) into real backend workflows

How I approach building

  • Prefer simple, explicit architectures over clever abstractions
  • Treat production behavior as the ultimate truth
  • Design systems to be observable, debuggable, and predictable
  • Integrate AI where it improves outcomes, not where it adds complexity
  • Optimize for long-term maintainability, not short-term speed

Core skills

Languages & Backend

Go (advanced)PythonTypeScriptSQLREST APIsConcurrency

Distributed Systems

MicroservicesClean architecture and modular designReliability under loadFailure handling and system boundaries

Data & Messaging

Relational databases (PostgreSQL, MySQL)Caching (Redis)Messaging (RabbitMQ)Async workflows

Cloud & Platform

Containerized servicesKubernetes-based deploymentsDockerHelmGCPAzure

CI/CD & Observability

Automated pipelinesGitHub ActionsJenkinsSafe and repeatable deploymentsPrometheus, Grafana, ELKProduction debugging and operability

AI Systems

LLM integrationRetrieval-Augmented Generation (RAG)Agent-based and workflow-oriented architectures

Experience

  • Senior Software Developer at Capgemini since January 2025
  • Platform Configuration Owner since March 2026, accountable for configuration repositories, Helm charts, CI/CD pipelines, GitOps maintenance, and QA test setup
  • Designed and delivered Go-based services running in Kubernetes environments
  • Owned service reliability, release pipelines, deployment processes, on-call work, and incident response
  • Introduced Prometheus metrics, structured logging, and distributed tracing to improve incident triage
  • Contributed to OpenKCM with modular APIs and extensions

Selected work

  • SmartLearn AI — An LLM-powered learning application using retrieval-augmented generation, embedding-based semantic search, context retrieval, and prompt orchestration.
  • RitualOps AI — A system for orchestrating AI-driven workflows and long-running processes, with modular task execution, state management, inter-step coordination, and multi-tenant configuration.
  • Operational backend platforms — Backend systems automating provisioning and operational workflows, built with Go, clean architecture, and cloud-native deployment patterns.

Research & writing

I explore how intent, context, and structure can make AI systems more predictable and explainable.

Intentional Context Networks (ICN)

A proposed intent- and context-driven communication model for multi-agent AI systems, focused on predictability, coordination, and explainability beyond tool-centric approaches.

Oleg Grishanovich

Senior Golang Backend Engineer open to backend-focused interviews, production ownership roles, and selected contract work.

Email: oleg.grishanovich@outlook.com

Build: v2.0.0

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