# German Arutyunov — Principal Engineer > Principal Engineer with 7+ years across fintech and SaaS. AI-native development, distributed systems, micro-frontend architecture, cloud infrastructure, and engineering leadership. ## About Based in Malaga, Spain. Currently Principal Engineer at TradingView (since Jan 2025; promoted from Team Lead in Apr 2026). Master's in Data Analysis and Financial Technologies from HSE Moscow (2017–2023, GPA 8.0). Open to engagements that combine AI-native product delivery, resilient infrastructure, and engineering leadership. ## Contact - Email: germanarutyunov@gmail.com - GitHub: https://github.com/gaarutyunov - LinkedIn: https://linkedin.com/in/german-arutyunov/ - CV (docx): /German_Arutyunov_CV.docx ## Areas of expertise ### AI (1y) AI-native development, agentic systems for ops & engineering AI-native development approach grounded in a Master's in Data Science and Financial Technologies. Designed and deployed agentic systems to streamline operations and accelerate software development workflows. Highlights: - Apply AI-native practices across the full engineering lifecycle - Design and deploy agentic systems that automate complex operational workflows - Approach AI with a scientific rigour — Master's in Data Science underpins every model decision - Bring a systems engineering lens to AI: reliability, observability, failure modes Stack: AI-native, Agentic Systems, LLM Integration, PyTorch, MLX, Fine-tuning, NLP, MLOps #### Scientific foundation A Master's in Data Analysis and Financial Technologies from HSE means AI is not a buzzword — it's a discipline. Model selection, evaluation methodology, and statistical rigour are built into how I approach every AI problem. #### Agentic systems Designed and deployed systems where AI agents take on real operational workloads — not demos, but production systems with real business impact. - Autonomous agents for operations: alert triage, runbook execution, incident response - Development workflow agents: PR review, test generation, architecture validation - Multi-step reasoning pipelines with tool use, memory, and structured output - Evaluation frameworks to measure and improve agent reliability over time #### The engineering lens AI systems require the same engineering discipline as any other production system — reliability, observability, failure modes, and graceful degradation. - Fine-tuned open-weights models matching commercial LLM quality at lower cost - LLM integration patterns: streaming, tool use, structured output, caching - Evaluation and feedback loops built into the deployment lifecycle - Cost, latency, and reliability tradeoffs navigated with production constraints ### leadership (5y) People-oriented, agile, strong stakeholder management People-oriented leader who finds each person's strengths to benefit the team. Agile mindset — moves fast and adapts to challenges. Result-oriented with strong stakeholder management skills that navigate corporate environments to bring projects to life. Highlights: - Find each person's strengths and channel them toward shared goals - Move fast with an agile mindset — adapt priorities as challenges evolve - Navigate stakeholder dynamics to unblock and ship projects that matter - Deliver results even in complex, politically charged environments Stack: Agile, People Management, Stakeholder Management, Team Building, Result-Oriented, Mentorship #### People first Great engineering output comes from people who feel seen and have their strengths channeled toward meaningful work. I lead by understanding each individual first — their motivation, their working style, what makes them sharp — and then designing a team dynamic that amplifies that. #### Delivery mindset Leadership without results is just management. I combine a people-first approach with an unwavering commitment to shipping — even when the environment is corporate, slow, or politically complex. - Agile without dogma: adapt the process to the team, not the team to the process - Stakeholder alignment before, during, and after — no surprise pivots - Unblocking teams by navigating org dynamics rather than fighting them - Moving fast by making the right calls early and correcting course quickly #### What I bring to a team Whether leading from the front or enabling others to lead, I orient toward the outcome: a team that works well together and ships things that matter. - Clarity of direction — people should never wonder what success looks like - Psychological safety — the team speaks up, experiments, and learns - A bias toward action combined with discipline in prioritization - Mentorship and career growth as a shared responsibility, not an afterthought ### backend (7y) Horizontally scalable, high-availability, geographically distributed systems Designed and built complex horizontally scalable, geographically distributed systems in Go and C#. Used and deployed PostgreSQL, Elasticsearch, Redis, and Kafka in production — both in application code and infrastructure. Highlights: - Design horizontally scalable, high-availability systems spanning multiple geographic regions - Build event-driven architectures with Kafka for high-throughput data pipelines - Implement full-text search with Elasticsearch at production scale - Reach for the right tool — PostgreSQL, Redis, Kafka — and operate it in production Stack: Go, C#, PostgreSQL, Elasticsearch, Redis, Kafka, gRPC, REST #### Systems I designed Geographically distributed systems that scale horizontally — built to handle real production load with real failure modes. Not just code that works on a laptop, but services that run in multiple regions with consistent guarantees. #### Data infrastructure Used the right tool for each job — and then operated it in production myself. - PostgreSQL for relational data with complex query patterns and JSONB - Elasticsearch for full-text search, aggregations, and analytical queries - Redis for low-latency caching, pub/sub, distributed locks, and rate limiting - Kafka for durable event streaming and decoupled service communication #### Languages & patterns Go for high-throughput services where performance and simplicity matter. C# for complex domain logic and enterprise integrations. - Go: goroutines, channels, context propagation, graceful shutdown - C#: async/await, dependency injection, Clean Architecture, domain-driven design - gRPC for internal service communication with schema-first contracts - Idempotent consumers and exactly-once processing patterns with Kafka ### devops (7y) Kubernetes internals, cloud migrations, multi-cloud CI/CD Can navigate Kubernetes source code and understand its architecture. Migrated complex systems across clouds, from Nomad to Kubernetes. Developed flexible CI/CD pipelines that work across multiple clouds, regions, and topologies. Highlights: - Navigate Kubernetes source code and understand its internals - Lead full cloud migrations — cross-cloud and Nomad → Kubernetes - Build CI/CD pipelines that adapt dynamically to any cloud, region, or topology - Own the full infrastructure stack — not just the YAML, but the actual operations Stack: Kubernetes, Nomad, CI/CD, Multi-cloud, Cloud Migration, Helm, Terraform, Docker #### Kubernetes depth Kubernetes is not just a deployment target — I understand how it works internally. This means I can debug obscure scheduler behavior, understand what a controller is actually doing, and make informed decisions about resource configuration rather than guessing. #### Migrations Migrated production systems with real users and real constraints. - Nomad → Kubernetes migration: zero-downtime, multi-service, multi-team coordination - Cross-cloud migrations preserving data integrity and minimizing blast radius - Networking and DNS topology changes across migration boundaries - Rollback planning and live traffic validation at each stage #### CI/CD Built pipelines designed to be extended, not just used. The goal: a single pipeline definition that works across any cloud, region, or environment — no forking, no duplication. - Dynamic environment targeting based on branch, tag, or environment variable - Multi-cloud deployment steps with environment-specific secret injection - Parallel deployment strategies across regions with health gate validation - Rollback automation triggered by metric thresholds post-deploy ### frontend (8y) Complex B2B platforms with micro frontend architecture Built a complex B2B platform from scratch with a high abstraction level supporting multiple financial products. Applied cutting-edge micro frontend architecture with Webpack Module Federation. Highlights: - Architect B2B platforms from scratch with high abstraction across multiple product lines - Apply Webpack Module Federation for true runtime micro frontend composition - Design shared component systems consumed across independently deployed micro apps - Ship production Angular at scale with robust state management Stack: Angular, Micro Frontend, Module Federation, Webpack, TypeScript, RxJS #### What I built A complex B2B platform from scratch, supporting multiple financial products through a high-abstraction shared design system. The platform was designed so individual product teams could ship independently while composing seamlessly at runtime. #### Architecture Micro frontend architecture using Webpack Module Federation — each financial product as a separately deployed remote, composed dynamically into a shell. - Shell application orchestrating dynamic remote loading at runtime - Shared design system and utility library consumed across all remotes - Federated routing and authentication with zero coupling between products - Independent CI/CD pipelines per remote — deploy without coordination #### Key skills demonstrated This project required deep knowledge of the entire frontend stack — from Webpack internals to Angular dependency injection to module resolution. - Webpack Module Federation configuration and optimization - Angular architecture patterns: lazy loading, feature modules, DI - TypeScript at scale: generics, type guards, shared type contracts - Performance budgeting and bundle analysis across federated modules ## Experience ### TradingView — Jan 2025 – Present Location: Hybrid, Malaga, Spain Roles: Principal Engineer (Apr 2026 – Present) · Team Lead (Jan 2025 – Apr 2026) - Developing internal AI platform to accelerate product and software development lifecycle processes [ai] - Designed and developed 2 new products end-to-end, expanding the company's portfolio [leadership, ai] - Optimised team processes accelerating delivery by 30% [leadership] - Founded the Engineering Committee driving 5 global initiatives across CI/CD, telemetry, architecture, and integration testing [leadership, devops] - Built an AI Skills Library embedding AI tooling into the SDLC; ran adoption workshops across engineering teams [ai, leadership] - Prototyped AI-native products to streamline roadmap prioritisation [ai] - Fine-tuned open-weights models for data enrichment pipelines, matching commercial LLM quality at lower cost [ai, backend] ### SimplyFi — May 2023 – Jan 2025 Location: Dubai, UAE Roles: CTO - Led platform adaptation for 3 international markets (Russia, UAE, KSA) across YandexCloud, AWS, and GCP [devops, leadership] - Reduced infrastructure costs by 50% via cloud migration to managed services [devops] - Led the development and integration of 4 new fintech products for SMEs into the platform [backend, leadership] ### SimpleFinance Group — Aug 2019 – May 2023 Location: Moscow, Russia Roles: Team Lead · Senior Software Developer - Designed micro-frontend architecture (Webpack Module Federation, Angular 12, NgRx) — 5× faster builds, 50% faster development [frontend] - Built CLI tooling in Go for micro-frontend workflows, cutting boilerplate and increasing dev speed by 20% [backend, frontend] - Led Kubernetes migration improving system maintainability by 30% and enhancing scalability [devops] - Reduced downtime by 40% via comprehensive monitoring, alerting, and high-availability infrastructure [devops, backend] - Recruited and mentored a team of 15 engineers, QA, and analysts [leadership] ### Loyalty & Media Group — Aug 2018 – Aug 2019 Location: Moscow, Russia Roles: Senior Frontend Developer - Senior frontend engineering role building loyalty and media products [frontend] ## Education ### Higher School of Economics — 2017–2023 Moscow, Russia. Master's Degree in Data Analysis and Financial Technologies. GPA 8.0. ## Links - [Home](/) - [CV](/cv) - [AI](/ai): AI-native development, agentic systems for ops & engineering - [leadership](/leadership): People-oriented, agile, strong stakeholder management - [backend](/backend): Horizontally scalable, high-availability, geographically distributed systems - [devops](/devops): Kubernetes internals, cloud migrations, multi-cloud CI/CD - [frontend](/frontend): Complex B2B platforms with micro frontend architecture