Vetted Full Stack Developers in California

Harsh Sanas

Screened

Intern Full-Stack Engineer specializing in AI and distributed systems

Los Angeles, CA2y exp

“Full-stack product engineer who has designed and shipped production web experiences in EV charging, trading, automotive companion apps, and AI systems. Stands out for owning user-facing React experiences through backend integration and production monitoring, with a strong bias toward reliability in real-time and high-stakes workflows. Also has early-stage Scale AI experience building a Text-to-SQL agent stack with Python, PostgreSQL, Redis, Kafka, and AWS.”

Akhil Jaggari

Screened

Mid-level Full-Stack Software Engineer specializing in scalable web platforms and cloud microservices

CA, CA6y exp

“Backend engineer with fintech/real-estate lending domain experience (Berkadia) building Python/Flask services for indicative loan pricing across Fannie/Freddie workflows. Strong in scalable AWS architectures (S3, Lambda, SageMaker), database performance (PostgreSQL read replicas, indexing, pooling), and high-throughput optimizations (streaming exports, Redis caching) with measurable production impact.”

“Software engineer focused on reliability and scalable systems: built React/TypeScript dashboards backed by Java/Spring Boot APIs and designed Kafka-based microservices with strong contract/versioning discipline. Known for shipping incremental improvements with tight feedback loops and for creating internal observability tools that streamline on-call and incident diagnosis under high-traffic conditions.”

ABHIJOY SARKAR

Screened

Senior AI Engineer specializing in LLMs, agentic systems, and MLOps

San Francisco Bay Area, CA8y exp

“Built and shipped PromptGuard, a production middleware proxy that secures GenAI RAG/agent systems against prompt injection and unsafe tool use using risk scoring, graded policy actions, and least-privilege tool gating. Also replaced LangChain abstractions with a custom state-machine runner for a production voice agent to reduce latency and improve traceability, and delivered a clinic call assistant by converting front-desk/doctor requirements into scenario-based guardrails and measurable evals.”

“Backend/data engineer focused on compliance and statistical processing systems on AWS, building containerized FastAPI services plus event-driven async workflows (Step Functions/EventBridge) with strong reliability patterns (JWT auth, idempotency, structured logging). Has modernized SAS-based batch pipelines into modular Python/AWS services with parallel-run parity validation, and has demonstrated measurable SQL performance wins (40+ min to <10 min) and hands-on incident ownership using CloudWatch-driven detection and prevention.”