Adrian User
@adrianuser8
I’m a full-stack and AI engineer building reliable RAG and security systems where correctness and trust matter.
What I'm looking for
I’m a Full-Stack and AI Engineer with 8+ years of experience across real-time payments, enterprise AI, and autonomous security products. My work focuses on RAG systems, PostgreSQL-native vector search, LLM flows, and backend product architecture—especially where mistakes affect money, security, compliance, or customer trust.
In my recent role, I advanced the validation and execution layer of an autonomous offensive security platform. I built deterministic exploit-validation flows so reported findings had to reproduce against the actual target before reaching customer-facing dashboards, and I orchestrated Kubernetes-based agent lifecycle, task queues, and result aggregation across isolated customer environments.
Before that, I delivered RAG engineering for a knowledge assistant that indexed years of project reports and architecture decisions for grounded natural-language search. I standardized PostgreSQL-native RAG into pgRAG using pgvector, improved retrieval via chunking strategies, and built LLM enrichment flows while raising client handoff quality through clear architecture decisions and practical maintenance guidance.
Experience
Work history, roles, and key accomplishments
Full-Stack and AI Engineer
XBOW
Apr 2024 - Mar 2026 (1 year 11 months)
Advanced the validation and execution layer of the XBOW Autonomous Offensive Security Platform, orchestrating parallel AI agents to discover, validate, and confirm vulnerabilities within approved customer scopes. Built deterministic exploit-validation flows and Kubernetes-based agent lifecycles that generate reproducible evidence for security dashboards.
Delivered engineering contributions to Wilde, NearForm's internal RAG knowledge assistant for grounded natural-language search over project reports and architecture decisions. Designed retrieval and ingestion patterns using PostgreSQL and pgvector (pgRAG), and built an LLM-driven sales intelligence flow (Beckett) to enrich prospect research before business development.
Built checkout and reconciliation components for Pay with Ibotta, enabling real-time discounts at the point of sale. Implemented transaction logic and retailer POS API integrations using Ruby on Rails, React, and PostgreSQL, and applied PCI DSS requirements for tokenization and audit trails.
Education
Degrees, certifications, and relevant coursework
Warsaw University of Technology
Bachelor of Science, Computer Science
2013 - 2017
Bachelor of Science in Computer Science at Warsaw University of Technology from 2013 to 2017.
Tech stack
Software and tools used professionally
Availability
Location
Authorized to work in
Job categories
Skills
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