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AI Engineer with 3+ years in AI Model Evaluation & Data Labeling
AI is analyzing your overall score…
Identifying your key strengths…
Evaluating your skill match against the job requirements…
Assessing your cultural and operational fit
AI Engineer with 3.1 years of experience, specializing in AI model evaluation, data labeling, and prompt engineering. Proven ability to improve AI model reliability, streamline operations, and lead teams in complex data environments. Recognized for outstanding performance in Retrieval-Augmented Generation and prompt optimization projects at Amazon Web Services.
SSR College of Arts, Science and Commerce, Silvassa
Bachelor of Business Administration (BBA)
June 1, 2018 – May 1, 2021
Amazon Web Services (AWS)
ML Data Associate I
November 1, 2024 – Present
Bengaluru, Karnataka, India
Kotak Mahindra Bank Ltd
Credit Processing Associate (CPA)
March 1, 2023 – August 1, 2024
Vapi, Gujarat, India
Team Captain - Company Ideathon Hackathon
Unknown
September 1, 2025 – Present
Prime Member R&R Award - ASPO Prompt Optimization
Amazon AWS
August 1, 2025 – Present
Prime Member R&R Award - RAG Output Evaluation
Amazon AWS
April 1, 2025 – Present
Cultural Fit Analysis
The candidate's experience at AWS, a leading tech company, and their involvement in an Ideathon suggest an inclination towards innovation and a fast-paced, tech-driven culture. Their leadership roles and awards indicate a proactive and results-oriented mindset. The transition from a financial role to an AI-focused role at AWS demonstrates adaptability and a strong interest in the AI domain, aligning with a culture that values continuous learning and growth. However, the lack of diverse project experience outside of their current role limits the full assessment of cultural fit across varied team dynamics.
Soft Skills & Operational Fit
The candidate demonstrates strong soft skills in team leadership, cross-functional collaboration, and process improvement, evidenced by their role as Team Lead at AWS and their involvement in an Ideathon. Their ability to create SOPs and conduct root-cause analysis indicates a methodical and quality-oriented approach, which is beneficial for operational fit in an AI engineering role. The experience in a banking environment also suggests an ability to work within regulated frameworks and manage detailed processes.