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Vetted FastAPI Professionals
Pre-screened and vetted.
Senior Data Scientist specializing in ML, fraud risk, and Generative AI (RAG/LLMs)
Junior Full-Stack Software Engineer specializing in data-driven web apps and cloud platforms
Mid-level AI/ML Engineer specializing in GenAI, computer vision, and real-time ML pipelines
Senior Full-Stack AI/ML Engineer specializing in personalization, NLP, and GenAI platforms
Mid-level Full-Stack Java Developer specializing in cloud-native microservices
Junior Front-End/Full-Stack Software Engineer specializing in accessible web applications
Mid-level Data Scientist / ML Engineer specializing in LLMs and predictive analytics
Mid-level Full-Stack Developer specializing in React and Python (Django/FastAPI)
Senior Data Engineer specializing in cloud data platforms and real-time streaming pipelines
Senior Full-Stack Developer specializing in cloud-native microservices (AWS)
Senior Data Scientist specializing in healthcare analytics and scalable ML pipelines
Deeksha V
Mid-Level Software Engineer specializing in cloud data platforms and FinTech payments
“Backend engineer focused on financial systems, having evolved payments and reconciliation platforms using Python/FastAPI and PostgreSQL with an emphasis on idempotency, validation, and consistency. Has led monolith-to-services migrations using feature flags and shadow traffic, and implements defense-in-depth security (OAuth2/JWT plus DB-level row security) for multi-tenant environments.”
KrishnaVarshith Pabbisetty
Mid-level Backend Software Engineer specializing in Spring Boot, microservices, and cloud-native AI
“Backend engineer with experience modernizing a large-scale procurement platform at Jio Platforms by breaking a monolith serving 35 business units into Spring Boot microservices, improving uptime and cutting report latency ~30%. Also built high-concurrency FastAPI systems (200ms at ~500 concurrent users) with strong security (JWT/OAuth2/RBAC), event-driven Kafka integrations, and reliability patterns like exactly-once delivery for ~1M monthly triggers.”
Emmanuel Ngalima
Mid-Level Software Engineer specializing in geospatial AI and cloud security automation
“Cloud engineer and cloud OS SME (Chevron) who productionized large-scale security remediation—using Tanium and Ansible to address CIS benchmark noncompliance across 5,000+ servers with robust logging and RCA handoffs. Also drives adoption of a geospatial AI refinery inspection product by consolidating siloed imagery into an enterprise geospatial database, and presents internally on agentic/LLM tooling (LangChain/LangGraph, LangSmith observability).”
Rafael Ortega
Senior Full-Stack & AI Engineer specializing in LLM integrations and cloud-native systems
“Backend/data engineer with hands-on production experience building FastAPI Python APIs and AWS-native platforms (Lambda/API Gateway, SQS, ECS Fargate) with Terraform + GitHub Actions CI/CD and strong reliability practices (JWT/RBAC, retries/timeouts, structured errors/logging). Also built AWS Glue ETL pipelines (S3/RDS to curated S3/Athena) with schema evolution and data quality controls, modernized legacy processing via parallel-run validation and phased cutovers, and has demonstrated SQL tuning impact (seconds to <200ms) plus incident ownership for batch pipeline SLAs.”
Pavan Kalyan
Mid-level AI Engineer specializing in GenAI agents and RAG for IT operations
“Built and operates a production LLM agent for enterprise IT operations that triages and drafts resolutions for high-volume ServiceNow tickets using LangChain + RAG (Pinecone/pgvector) and AWS Bedrock/OpenAI. Emphasizes reliability with schema-validated stages, offline eval datasets from real tickets, and CloudWatch-driven monitoring/guardrails; system scales to 40K+ tickets/month and cut resolution time ~28%.”