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AI Engineer with 10+ years in AI/ML, Backend, and Data Engineering
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Assessing your cultural and operational fit
Senior Python Engineer with over 10 years of experience building backend services, AI-enabled platforms, APIs, data pipelines, and scalable production systems across fintech, fraud/risk, SaaS, and analytics environments. Strong hands-on background in Python, FastAPI, REST APIs, RAG systems, LLM integrations, MCP-style tool exposure, AI guardrails, evaluation workflows, AWS, Docker, Kubernetes, PostgreSQL, Redis, CI/CD, testing, and production operations. Experienced in owning projects end-to-end, gathering requirements from technical and non-technical stakeholders, mentoring engineers, and helping teams adopt reusable AI capabilities safely and effectively.
University of Latvia
Bachelor of Science · Computer Science
August 1, 2011 – June 30, 2015
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Cultural Fit Analysis
The candidate shows a strong cultural fit through diverse project experience across various industries (fintech, fraud/risk, SaaS, analytics, trading), suggesting adaptability. Their current role as 'Senior Python Engineer / AI Engineer' and a clear career progression towards AI engineering demonstrate strong alignment with the target role. The emphasis on collaboration, mentorship, and owning projects from conception to deployment indicates a proactive, team-oriented, and responsible work ethic. Experience with multiple cloud providers and modern development practices (Agile, CI/CD) further supports a fit for dynamic, technically advanced environments.
Soft Skills & Operational Fit
The candidate demonstrates strong leadership and mentorship capabilities, evidenced by leading engineering work and mentoring peers. They exhibit excellent cross-functional collaboration skills, working with product managers, data teams, and DevOps. A clear focus on end-to-end ownership, system design, scalability, reliability, and quality assurance (including AI evaluation and guardrail testing) indicates a mature operational fit. The ability to translate requirements into reliable engineering deliverables and drive architectural decisions further highlights their senior-level operational readiness.