Available to hire
Hello! I’m Krishnacharan Bhola, a software engineer with 2+ years of experience building and maintaining scalable data processing systems in cloud-native environments. I focus on Python, SQL, distributed systems, and event-driven architectures to ensure data reliability, performance, and correctness.
I enjoy collaborating with cross-functional teams, designing reliable architectures, and delivering measurable improvements in system latency and throughput. I’ve shipped end-to-end services, integrated AI capabilities, and implemented robust testing and monitoring to keep production systems resilient.
Skills
Work Experience
Software Engineer at Venu AI
May 1, 2025 - December 1, 2025Built and owned Python/FastAPI microservices supporting autonomous campaign workflows, reliably processing 1M+ events/day in production. Designed event-driven architectures using Celery, DynamoDB, and cloud messaging to orchestrate background jobs at scale. Integrated LLM-powered content generation into live systems, improving engagement metrics by 22%. Implemented retry logic, idempotency, and monitoring to reduce failed jobs by ~30% under peak load. Worked directly with founders on system design decisions, roadmap planning, and scaling strategies for a high-growth B2B platform.
Software Engineer at Dentite
January 1, 2025 - May 1, 2025Developed backend services and APIs for an AI-driven OCR application, converting unstructured insurance data into structured records. Collaborated with data science teams to optimize inference pipelines, reducing model latency by 30%. Designed validation and error-handling logic that reduced data extraction errors by ~20% in downstream workflows. Implemented secure storage and REST APIs in a regulated, production healthcare environment.
Software Developer at NICE CXone
January 1, 2024 - July 1, 2024Evaluated real-time streaming architectures (AWS Kinesis, SQS, SNS) for latency-sensitive systems and delivered quantitative benchmarks. Built a production-ready proof of concept that informed architecture decisions and reduced projected cloud costs by ~20%. Debugged and resolved production issues using logs and metrics, reducing MTTR by ~40%. Improved projected system scalability by 25% through stream partitioning, batching, and network optimizations.
Education
Master of Science in Computer Science and Engineering (AI/ML) at State University of New York, Buffalo
January 11, 2030 - December 1, 2025Bachelor of Science in Computer Science and Engineering at Walchand College of Engineering, India
January 11, 2030 - May 1, 2024Qualifications
Industry Experience
Software & Internet
Skills
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