.png){kind=logo}
NK
Narayana Koushik kancharla
Intern Data Scientist specializing in Generative AI and NLP
United StatesAi agent developer - Internship2 years experienceInternTechnologyArtificial IntelligenceHealthcare
ScreenedIdentity Verified
Connect with Narayana
Narayana already has a relationship with Reval, so a warm intro from us gets a much better response than cold outreach.
Recommended
Already have an account?
About
Backend/AI engineer with internship experience building an AI-powered financial insights platform (FastAPI, Redis, BigQuery) and prior HCL experience leading a monolith-to-microservices refactor (Flask, Kafka) using blue-green deployments. Demonstrates strong performance/security focus (OAuth/JWT/RBAC, encryption) and measurable impact on latency, downtime, and ML model reliability; MVP was submitted to Google’s accelerator program.
Experience
Ai agent developer - InternshipLillup
generative ai internSocial Work Wealth Conference
Senior Software EngineerHCL
InternHCL
Education
University of New Havenmaster, Data Science (2025)
Sathyabama Institute of Science and Technologybachelor, Electronics and Communication Engineering (2022)
Key Strengths
- Designed scalable, low-latency FastAPI backend using Redis + BigQuery; reduced response time ~40%
- Built data validation layer with TensorFlow Data Validation to catch anomalies and prevent schema/latency issues
- Improved API performance and stability via async processing and Redis key-expiration tuning (avg latency ~1.8s to ~1.0s)
- Led monolith-to-microservices refactor using Flask and Kafka with blue-green deployment and versioned APIs; reduced downtime 62%
- Implemented production security: Google OAuth, JWT, RBAC via dependency injection, query-level row security, AES encryption, HTTPS/CORS
- Identified ML edge case (neutral misclassified as positive); improved sentiment accuracy 78% to 85% using stratified sampling + confidence thresholds
- Built and deployed a production LLM-based personalized AI tutor (financial education) with citations/safety focus
- Performance optimization on Cloud Run (request batching, TTL caching, warm pool, token streaming) reducing latency from ~2.8s to ~1.1s
- Designs reliable AI workflows with SLAs/KPIs, modular components, and robust testing (unit/integration, synthetic data)
- Experienced orchestrating ML/GenAI pipelines with Airflow and AWS Step Functions (dependency management, retries, alerting, scalable components)
- Strong model/retrieval selection approach (dense vs sparse vs hybrid; cost/latency tradeoffs; prompting iteration)
- Effective collaboration with non-technical stakeholders via workshops, prototypes, and dashboards; aligned AI objectives to domain goals
Discover more candidates like Narayana
Search across thousands of pre-screened, high-quality, high-intent candidates on Reval.
Search Talent