Offer / software engineering / AI and cloud

Practical engineering support from AI adoption to production operations.

I help companies turn technical uncertainty into shipped, maintainable systems: AI workflows, cloud infrastructure, full-stack products, monitoring, and team enablement.

Start a conversation

AI implementation across the company

I help identify useful AI workflows, connect company knowledge, design agent and RAG systems, and take them from prototype to secure, observable production use.

Workflow discovery and technical strategy
RAG, agents, AI gateways, and internal tools
Deployment patterns, governance, and adoption support

Infrastructure review and setup

I review cloud environments, deployment paths, access boundaries, and operational risk, then build or improve the infrastructure needed for reliable delivery.

AWS, GCP, Kubernetes, serverless, and networking
Terraform, CI/CD, secrets, identity, and permissions
Cost, reliability, security, and observability reviews

Full-stack delivery with production-grade deployments

I deliver backend, frontend, integration, and data-layer work with the release path included, so the result is deployable and maintainable.

Java, TypeScript, Python, Spring, NestJS, React, and Svelte
APIs, microservices, BFFs, asynchronous workers, and databases
Testing, build pipelines, deployment automation, and handover

Maintenance and monitoring

I help keep systems healthy after launch by improving observability, release hygiene, incident readiness, dependency updates, and operational feedback loops.

Logs, metrics, alerts, dashboards, and runbooks
Production fixes, dependency updates, and release support
Operational reviews and practical reliability improvements

Tutoring and training for people and teams

I run focused technical sessions for individuals and teams who want to understand modern AI, cloud, backend, full-stack, or DevOps practices through real engineering examples.

One-to-one tutoring and team workshops
AI implementation, cloud, infrastructure, and coding practices
Hands-on formats shaped around the team's current work