KANISHK SHARMA

AI Engineer

https://www.opentalent.in/kanishk-sharma

RAIGARH, indiaMember since April 19, 2025

Key Strengths

Strong proficiency in GoLang for building scalable and efficient RESTful APIs and backend systems.
Demonstrated expertise in distributed systems, including Kafka for messaging and event-driven architectures.
Proven ability to optimize system performance, evidenced by significant reductions in API response times (e.g., 6s to 500ms, 20s to 2s) and cost savings (80% on Google Distance Matrix API).
Experience with Docker and Kubernetes for containerization and deployment, enhancing system responsiveness.
Solid understanding of system design principles (LLD, HLD, SOLID) and cloud platforms (AWS, GCP).
Quantifiable impact in previous roles, indicating a results-oriented approach and problem-solving capabilities.
For an AI Engineer role, the candidate possesses a strong software engineering foundation crucial for MLOps, AI infrastructure, and building robust AI-powered applications, but lacks direct AI/ML specific experience.

Cultural & Operational Fit

Cultural Fit Analysis

The psychometric test score of 0 raises significant concerns regarding cultural fit, work attitude, stress handling, and team collaboration. This score indicates either a failure to complete the assessment or a severe mismatch, requiring further investigation.

Soft Skills & Operational Fit

The candidate lists problem-solving, teamwork, adaptability, and communication as soft skills. Experience descriptions indicate collaboration with cross-functional teams and a focus on delivering user experience improvements. Operational fit is supported by experience with CI/CD tools (Github, Jenkins), Docker, Kubernetes, and system design principles.

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Evaluating your skill match against the job requirements…

Assessing your cultural and operational fit

Key Strengths

Strong proficiency in GoLang for building scalable and efficient RESTful APIs and backend systems.
Demonstrated expertise in distributed systems, including Kafka for messaging and event-driven architectures.
Proven ability to optimize system performance, evidenced by significant reductions in API response times (e.g., 6s to 500ms, 20s to 2s) and cost savings (80% on Google Distance Matrix API).
Experience with Docker and Kubernetes for containerization and deployment, enhancing system responsiveness.
Solid understanding of system design principles (LLD, HLD, SOLID) and cloud platforms (AWS, GCP).
Quantifiable impact in previous roles, indicating a results-oriented approach and problem-solving capabilities.
For an AI Engineer role, the candidate possesses a strong software engineering foundation crucial for MLOps, AI infrastructure, and building robust AI-powered applications, but lacks direct AI/ML specific experience.

Cultural & Operational Fit

Cultural Fit Analysis

Soft Skills & Operational Fit