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BENCH+ PROFILE

Dmitrii

AI Integration Engineer
Product-oriented full-stack AI integration with LLM APIs, TypeScript/Node.js, React/Next.js, Python ML/data components, and pragmatic MVP delivery

Staff-level product-oriented engineer suited to hands-on AI-enabled product delivery, combining full-stack implementation, API integration, technical leadership, CI/CD, testing, and stakeholder-facing delivery.

BEST-FIT USE CASE

AI-enabled SaaS or internal product initiatives that need a hands-on engineer to clarify product intent, design an MVP-oriented architecture, integrate LLM APIs, build full-stack features, and bring quality practices into the codebase.

Not the primary fit: Pure model research, dedicated MLOps ownership, security operations, or roles focused only on long-term people management without hands-on implementation.

EVIDENCE HIGHLIGHTS

What supports the assessment

01

Current work includes hands-on AI-enabled product implementation using TypeScript across front end and back end, with Python for ML/data components.

02

Prototyped computer-vision and generative features, including image generation, object detection, and video analysis for edge-device experiments.

03

Led mobile engineering around a React Native application and backend-for-frontend layers, addressing startup, rendering, latency, and payload issues.

04

Led frontend architecture and delivery improvements for contract product teams across gaming, real-estate, martech, and SaaS contexts.

05

Led modernization from a legacy Java web stack toward React/TypeScript and Java REST services, including reusable libraries, architectural foundations, generators, CI, automated testing, and review practices.

06

Contributed to microelectronics solutions with production C and hardware-description-language work, plus build and test automation.

07

Built desktop, low-level, microprocessor, and FPGA solutions earlier in the career.

WORKING STYLE

How they show up

  • Structures explanations around business logic, product needs, technical approach, and delivery outcomes.
  • Works both independently and in teams, including direct collaboration with international teams and stakeholders.
  • Clarifies requirements and discusses alternatives with clients or stakeholders when implementation direction needs adjustment.
  • Uses tests and review as part of quality control for both human-written and AI-assisted code.
  • Approaches new technology through practical task-based learning and implementation.