Lead &coach junior team memberswith best practices &largescale E2E testing.•Acted as the final gatekeeper for product releases, ensuring readiness eng leaders accountable.develop, finetune&optimize LLM-based solutions.Develop and deploy AI agent sol, leveraging AI Agent platform to create scalable templates for customers•Translate business goals into strategy, user experience and technical requirements in close collaboration with UX, Data Science, Engineering, AI research, and Product Marketing teams.Implement AIOps practices, including CI/CD pipelines, feature flagging, model monitoring &performance optimization.Lead multi-agent AI system design, integrating Retrieval-Augmented Generation (RAG) to improve data accessibility and automation.Work closely with enterprise customers and sales engineers to translate business reqts into deployable AI agent solutions.
• Build functional AI prototype using frameworks such as LangChain, Crew.AI and to optimize AI retrieval, processing, and inference.Involve in technical decisions by collaborating cross-functionally with productS, data scientists, and engineers to deliver AI-driven features aligned with business goals.Established quality metrics &dashboards for executive visibility, enablings data-driven decision-making.Designed, implemented&integrated quality frameworks, steering build vs. buy decisions for tooling and architecture.Deep expertise in LLM concepts including prompt engineering, AI feature evaluation metrics, model fine-tuning, knowledge of vector.Design best practices for AI-driven automation, ensuring compliance, security, and scalability.Skilled in Python and demos for stakeholders.
Developing stakeholder relationships, supporting plans, setting goals, and promoting continuous learning.Proficient with Docker (Grafana) logs.Skilled in GitHub&Git Action workflows.Proficient in Visual Studio, SpecFlow, feature files, utils, database access layers.Experience in data , GitActions, visualizations.
