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Harsh Sanas - Technical Advisor Intern (GenAI) in San Francisco, CA

Harsh Sanas

Junior Full-Stack Engineer specializing in AI systems and cloud applications

Scale AIUSCSan Francisco, CA2 Years ExperienceIntern LevelWorks On-Site

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About

Full-stack engineer with a strong applied AI bent who has built both a real-time EV charging platform and a production text-to-SQL system. Particularly compelling for teams needing someone who can bridge frontend, backend, infrastructure, and LLM evaluation/safety work, with experience shipping under early-stage ambiguity and integrating software with real-world hardware.

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Key Strengths

  • End-to-end full-stack ownership of EV charging features
  • Built real-time systems integrating web apps with physical chargers
  • Strong TypeScript-driven API and frontend contract design
  • Production AI feature delivery for text-to-SQL
  • Model benchmarking and selection using accuracy, latency, and cost
  • Grounded LLM system design with validation and safety checks
  • Production monitoring and regression analysis for AI systems
  • Improved schema grounding to raise execution accuracy without changing the model
  • Thoughtful human-in-the-loop design for high-risk AI workflows
  • Able to ship in ambiguous early-stage environments
  • Delivered a production-ready EV charging platform in about two months
  • Shipped production LLM agents with 99.5%+ uptime and sub-2-second latency
  • Delivered measurable business impact: 45% reduction in support handling time
  • Generated approximately $1.2M annual support cost savings
  • Improved customer satisfaction by 18%
  • Strong reliability engineering for LLM systems under API rate limits and latency spikes
  • Designed robust fallback and confidence-based escalation to human agents
  • Architected auditable multi-step agent workflows with structured outputs and state management
  • Built schema-validated, guardrailed integrations that prevented malformed data from breaking downstream systems
  • Data-driven evaluation and monitoring across offline tests and live production metrics
  • Improved live reliability by reducing fallback rates 30% through prompt and classifier iteration
  • Handled messy ERP integrations with normalization, data quality controls, and idempotent writes
  • End-to-end ownership of Python backend services for real-time telemetry systems
  • Designing robust state-reconciliation and idempotency to handle out-of-order/duplicate OCPP events
  • Building and operating Kubernetes deployments with Helm, probes, autoscaling, and zero-downtime rollouts
  • Implementing GitOps CI/CD with GitHub Actions + ArgoCD and fast rollback via Git revert
  • Planning and executing cloud-to-on-prem migrations using blue-green cutover and CDC with zero downtime
  • Designing Kafka streaming pipelines for bursty high-frequency data with ordering and deduplication controls
  • Improving ML forecasting reliability via better preprocessing and minimum-history thresholds

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Experience

Technical Advisor Intern (GenAI)Scale AI · Aug 2025 – Presentinternship
AI Software Engineering InternAmpure Charging Systems · May 2025 – Aug 2025internship
Full Stack DeveloperUltimate Scaler · Jun 2023 – Jun 2024
AI Software Engineering InternAmpure Charging Systems · May 2025 – Aug 2025internship

Education

USCmaster, Computer Science (2026)
University of Mumbaibachelor, Information Technology (2023)

Languages

English

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Harsh SanasJunior Full-Stack Engineer specializing in AI systems and cloud applications