Backend Engineer.
Systems-oriented backend engineer with a track record of rapid domain acquisition and production-grade delivery across genomics, finance, legal AI, and enterprise knowledge management. Consistent architectural approach across all domains: clean separation of concerns, protocol-based extensibility, event-driven patterns, and comprehensive observability. Currently building enterprise knowledge infrastructure on Azure.
Built to ship.
Every project exhibits the same design principles: clean separation of concerns, protocol-based extensibility, event-driven patterns, and comprehensive observability.
Autopod — Multi-Tenant Podcast Orchestrator
First Go code ever written — deployed as a multi-tenant production system with full test coverage and CI/CD.
- Control plane / data plane split: Go orchestrator drives a 7-step pipeline by calling stateless Python/FastAPI endpoints with typed HTTP contracts mirrored across languages
- Crash-resilient job state machine with SQLite persistence — every state transition writes to disk before proceeding, GetActiveJobs() resumes all in-flight jobs on startup
- Multi-tenancy by construction: per-customer watch directories, age-encrypted secrets decrypted at runtime, namespaced cloud storage on Cloudflare R2
- 21 Go tests + 36 Python tests, GitHub Actions CI with -race flag, Docker multi-stage builds
Memory Palace — Graph-Based Semantic Memory System
Personal/learning project. Query language design, graph databases, and the specification pattern — all learned from scratch for this build.
- Clean architecture with enforced layer boundaries: domain → infrastructure → services → api. Protocol-based interfaces for all external integrations
- Extensible query API using discriminated union specification pattern: 12+ composable spec types generating both Python predicates and Cypher WHERE clauses
- Type-safe Cypher query builder with state machine validating clause ordering at construction time
- Integrated as MCP server enabling Claude.ai to use the system as persistent external memory
Grimoire (SETS) — Enterprise Knowledge Management Platform
Enterprise evolution of Memory Palace, deployed on Azure at Wise. Same architectural DNA evolved for cloud infrastructure ownership and team-scale deployment.
- Deployed on Azure Container Apps with Bicep IaC: Neo4j AuraDB, Azure Container Registry, auto-scaling (scale-to-zero dev, 1–3 replicas prod)
- Full OAuth 2.0 authentication spanning three RFCs (7591, 8414, 9728) — Claude.ai MCP connector auto-negotiates auth, zero-config enterprise deployment
- Pluggable connector architecture: Confluence space indexing, GitHub repo analysis, code complexity metrics — all queryable through unified specification-based JSON DSL
- Enterprise features: JWT identity tracking, background job orchestration with APScheduler, liveness/readiness health probes
Sokrates IDR — Legal Document Intelligence Platform
Solo-built full-stack enterprise platform (estimated 4,000–8,000+ development hours by independent review).
- DDD with architectural boundaries enforced by import-linter contracts: domain → core → infrastructure → api. Repository pattern with protocol-based interfaces
- Polyglot persistence: PostgreSQL (asyncpg + SQLAlchemy + Alembic), Neo4j knowledge graph, MinIO document storage, PGVector embeddings
- OpenTelemetry with 13+ instrumentations, Logfire + Sentry + structlog for structured observability
- Comprehensive testing: pytest-asyncio, factory-boy, Playwright E2E. Automatic TypeScript client generation from OpenAPI specs
Impact across domains.
Forecast accuracy on 2.4B ISK cash flow volume
Compression ratio vs gzip for haplotype data
Improvement in transaction reconciliation
Solo development hours on Sokrates IDR
Professional experience.
Oct 2024 — Present
Backend Engineer
Wise (Iceland)
Enterprise knowledge management and internal tooling. Designed and deployed the Grimoire/SETS platform on Azure infrastructure for team use. Working with Microsoft Business Central integrations and connector development.
Aug 2022 — Sep 2024
Data Scientist & Business Intelligence Lead
Travelshift
Complete overhaul of data infrastructure, financial process automation, and predictive modeling for Iceland's largest travel marketplace.
- Kimball-dimensional star schema in Snowflake, ETL pipelines, Power BI reporting
- Cash flow forecasting with 0.42% margin of error on 2.4B ISK volume (6-month horizon)
- Automated payment reconciliation: 1-in-35 → <1-in-1,000 unreconcilable transactions
- Reduced booking department from 7 contractors to 2 while improving performance
May 2021 — Aug 2022
Data Analyst & Product Owner
Alfreð Atvinnuleit
Established BI environment with real-time dashboards. Product owner for gig economy freelancing platform. Authored grant proposal securing 30M ISK funding from Rannís.
2015 — 2017
Statistician & Bioinformatician
deCODE Genetics (Amgen)
Designed novel haplotype compression algorithm achieving >10× compression ratio versus gzip — enabled loading entire chromosomes into memory. Processed and analyzed large genetic datasets.
2018 — 2021
Instructor, Department of Computer Science
Reykjavík University
Taught while completing MSc: Programming, Data Structures, Calculus & Statistics, Discrete Mathematics II.
2013 — 2017
Founder
Taurus Supplements
Founded and operated a specialized supplement product line. End-to-end ownership: product development, manufacturing coordination, marketing, sales, and daily operations.
Tools and technologies.
Deep experience across the full stack, from architecture to observability.
Languages
Go (building proficiency — see Autopod), Python (expert), TypeScript/React, SQL, R, DAX/M
Backend & APIs
FastAPI, RESTful API design, OpenAPI specification, automatic client generation (Orval), WebSockets, Pydantic, dependency injection
Databases & Storage
PostgreSQL (asyncpg, SQLAlchemy, Alembic), Neo4j (Cypher, graph modeling), Snowflake, MinIO (S3-compatible), PGVector, SQLite
Cloud & Infrastructure
Azure (Container Apps, ACR, Bicep IaC, Databricks, Log Analytics), Docker (multi-stage builds, non-root), Cloudflare (R2, Tunnel), GitHub Actions CI/CD
Architecture & Patterns
Domain-Driven Design, clean/hexagonal architecture, specification pattern, repository pattern, event-driven design, control plane/data plane, Kimball-dimensional modeling
Observability & Quality
OpenTelemetry (13+ instrumentations), Logfire, Sentry, structlog, Ruff, basedpyright, Biome, import-linter, pre-commit hooks
Security
OAuth 2.0 (RFC 7591/8414/9728), JWT, bcrypt, age encryption, Google Cloud OAuth, CORS, non-root containers
AI & ML
LLM integration (Anthropic, OpenAI, Google Gemini), RAG systems, vector embeddings (Voyage AI), pydantic-ai, Claude Code, DBSCAN clustering
Data Engineering
ETL pipeline design, Microsoft Fabric, Power BI, PySpark, Celery distributed task queues, star schema design, data warehouse architecture
Academic background.
Reykjavík University · 2017 — 2021
Artificial Intelligence and Data Science. Thesis: Recommendation Systems.
University of Iceland · 2011 — 2016
Computational Mathematics and Computer Science.
Let's connect.
Looking for a backend engineer who ships production systems across domains? I'm always open to interesting conversations.