Vetted Flask Professionals

Srushti Milind Jamsandekar

Screened

Mid-Level Software Developer specializing in backend, cloud, and GenAI

CA, USA5y exp

“Full-stack engineer with fintech and AI feature experience who shipped an AI-powered project summary module in Next.js (App Router + TypeScript) with secure server-side fetching and route handlers to a FastAPI backend, then owned monitoring and performance fixes in production. Demonstrated measurable UX wins (30% faster dashboard loads) and strong backend fundamentals (Postgres indexing/EXPLAIN ANALYZE, SQS-orchestrated idempotent reconciliation workflows with DLQs and retries).”

Aditya Jaiswal

Screened

Intern Software Engineer specializing in cloud, DevOps, and applied AI

Carlsbad, CA1y exp

“Full-stack engineer with startup ownership experience (Aiir) building 15+ TypeScript/Go microservice APIs on GCP Cloud Run with Kafka-based async event streaming and React CRM integrations for billing/analytics. Strong post-launch operator who tuned Oracle performance (partitioning/indexing/query optimization) and validated a 23% retrieval-time reduction via AWR, and has a quality/DevSecOps mindset (94% Pytest coverage, GitHub Actions, SonarQube, Twistlock, CloudWatch) including migrating 18+ production CI/CD pipelines.”

Prasannakumar B Vardi

Screened

Senior Software Engineer specializing in low-latency ad targeting and distributed backend systems

Santa Clara, CA9y exp

“Backend/platform engineer who built a high-scale audience segmentation and real-time targeting system using Spark/Glue + S3/Hudi and low-latency API services backed by Redis/relational stores. Demonstrates strong production rigor: Spark performance tuning to eliminate OOM failures, API idempotency/caching to cut p95 latency ~40%, and careful dual-run/feature-flag migrations with reconciliation and rollback runbooks. Experienced implementing layered security with JWT/OAuth, RBAC/ABAC, and database row-level security to prevent privilege escalation.”

Vaibhav Sharma

Screened

Mid-level Software Engineer specializing in AI/ML and data platforms

Remote, USA5y exp

“AI/ML engineer who built a production agentic system to automate computational research experiments (simulation execution, parameter exploration, and numerical analysis) and mitigated context-window failures using constrained tool-calling/prompt-chaining patterns in LangChain with OpenAI tool-enabled models. Also has adtech/big-data pipeline experience at InMobi, orchestrating Spark jobs in Airflow to filter bot-like user IDs and publish clean IDs to an online NoSQL store for live serving, plus Apache open-source collaboration experience.”

Saksham Khatwani

Screened

Mid-level Software Engineer specializing in NLP and search systems

Aurora, United States3y exp

“Built an AI journaling app at HackCU 2025 featuring a speaking AI avatar with long-term memory via RAG (ChromaDB) and low-latency microservices coordinated through Kafka, including deployment under AMD/non-CUDA constraints using a quantized Llama 8B model. Also has Goldman Sachs experience deploying a Trade UI on Kubernetes with CI/CD rollback automation, plus a healthcare AI internship at CU Anschutz collaborating closely with physicians on diagnostic reasoning and dataset annotation.”

Suloni Praveen

Screened

Entry-Level Software Engineer specializing in data engineering and ML systems

Los Angeles, CA0y exp

“Built an end-to-end Next.js/TypeScript LLM-based scientific PDF analyzer using local Ollama/Llama inference to prioritize privacy and cost, producing structured research artifacts (e.g., authors/methods/findings) with ~92% extraction accuracy. At Qualtrics, helped replace a batch pipeline with a real-time, low-latency ML inference service (Python/Go on Kubernetes) using Redis caching, Grafana-based observability, and graceful fallbacks to protect UX during failures.”

Atharva Bhide

Screened

Entry Software Engineer specializing in AI/ML and multimodal systems

Los Angeles, CA1y exp

“Built and shipped a production healthcare AI platform for a clinic in Brea, LA that combined LLM-based clinical report generation, voice agents for appointment workflows, and camera-based patient monitoring. Stands out for pairing multimodal AI architecture with production-grade reliability and compliance practices, while delivering concrete business results including 90% workflow automation, 200 hours saved per month, and a 60% improvement in customer retention.”

“Early-career builder with hands-on project experience spanning Python data processing, a Chrome extension for autofilling job applications, and a sign-language glove system integrating sensors, microcontrollers, and a web interface. Stands out for approaching student and project work with a production-minded focus on validation, modularity, edge cases, and reliability.”

“Candidate is pursuing a CTO role and has helped multiple startups turn early technology concepts into concrete, real-world technical requirements. They cite a systems science and mathematics background, along with experience at JPMorgan Chase, and appear strongest in technical strategy, concept fleshing, and identifying strong people to help teams succeed.”

Amit Dharam

Screened

Junior AI/ML Software Engineer specializing in backend systems and cloud deployment

Tempe, AZ3y exp

“Built multiple end-to-end automation and data systems, including an Accio RAG pipeline combining PDF parsing, FastAPI, Neo4j, and vector search, plus Selenium-based scraping for a virtual try-on product. Stands out for reliability-minded engineering: automated testing, structured logging, validation layers, and a data-driven approach to debugging flaky automation that improved CI pass rates to over 98%.”

“AI/backend engineer who has owned production applied-ML systems end to end, including a Jitsi meeting intelligence platform with custom RoBERTa boundary detection, LLM summarization, and automated retraining from user feedback. Also has healthcare AI experience building a diabetes medication titration system with strict validation, drift monitoring, and safety guardrails—showing both product speed and high-stakes engineering rigor.”

“AI/LLM engineer with strong healthcare domain depth who has shipped production-grade agents for care coordination and clinical workflow automation. Stands out for combining Knowledge Graph RAG, LangGraph orchestration, and rigorous eval/guardrail systems to improve reliability in high-stakes environments, with measurable gains in review time, hallucination reduction, latency, and clinician adoption.”

“Full-stack product engineer who has built end-to-end apps and internal tools spanning React/TypeScript, Node/Express, and Postgres. Stands out for pragmatic shipping under ambiguity, creating reusable platform primitives like a centralized notification API, and designing safe multi-tenant configurable dashboards with schema validation.”

“Product-minded full-stack engineer with experience shipping engagement features and core communication systems at DribbleUp and Expys. Stands out for combining rapid MVP execution with rigorous iteration: delivered a leaderboard feature that lifted engagement by 8% initially and 20% overall, built a chat MVP in 3 days, and has hands-on experience deploying LangChain-based concierge agents with evals and human review.”

“Built full-stack features for an AI healthcare copilot at Prompt Opinion, combining React/Next.js, Node/Express, PostgreSQL, and LLM/MCP integrations over FHIR-compliant patient data. Stands out for healthcare data interoperability knowledge, production ownership, and measurable impact, including scaling chatbot throughput and improving model response accuracy by 30% through better MCP tool architecture.”

“Backend/data engineer focused on AWS-based Python services and data pipelines: built a Django/DRF user management/auth platform deployed with serverless AWS (Lambda/API Gateway) and event-driven workflows (Step Functions/EventBridge), with CloudFormation + Jenkins for automated delivery and Secrets Manager/Parameter Store for secure config. Also delivered AWS Glue ETL from S3 to RDS with schema evolution controls and incident-driven improvements, and has demonstrated measurable SQL tuning impact (minutes-to-seconds).”

“Senior frontend engineer with experience leading high-impact React/TypeScript products at HelloFresh and CAA, including an A/B-tested onboarding flow shipped across multiple international brands. Modernized a legacy .NET frontend to Next.js using SSR and performance techniques (caching/memoization/lazy loading) and implemented robust testing/monitoring (Cypress, Honeycomb, GA) in fast-paced, production-deploy environments.”

“Backend engineer focused on building production-ready Python services (Flask/FastAPI) with strong performance and scalability instincts—Celery/Redis background processing, robust multi-tenant isolation (Postgres RLS), and pragmatic CI/Docker operations. Demonstrated measurable DB optimization impact (cut a critical analytics query from ~1–2s to ~100–150ms) and has hands-on experience integrating LLM/ML workflows (OpenAI, LangChain, embeddings, Redis/FAISS vector stores) without degrading API responsiveness.”

“Built a production AI-driven QA automation platform using a multi-agent architecture (MCPs + LangGraph) to run parallel website tests across multiple device environments via automated image building and containerization. Currently collaborating with restaurant operators and managers to deliver an agentic restaurant analytics system, emphasizing deep domain discovery with non-technical stakeholders.”

“Backend/DevOps-focused engineer with healthcare and financial systems experience, including an ICU readmission risk platform delivering real-time ML scores via a secure FastAPI service (PyTorch model serving, PostgreSQL, Celery/Redis) deployed on AWS with strong observability. Has hands-on Kubernetes GitOps delivery (Helm, ArgoCD, HPA) and has supported a JPMC on-prem-to-AWS microservices migration using phased validation and blue-green cutovers, plus Kafka/Avro streaming for real-time transaction processing.”

“Head of Robotics at Orbital Composites who built the full ROS-based software stack ("OrbOS") for multi-robot KUKA-arm 3D printing of carbon-fiber composite geometries. Deep in motion planning and real-time control—created a pipeline to turn underconstrained toolpaths into optimal joint trajectories at massive command scale, plus redundant safety gatekeeping and a 250Hz synchronized robot+extruder controller. Has operated in a technical-founder capacity for ~6 years and values an engineering culture of openness, honesty, accountability, and high ownership.”

“Software engineer with strong end-to-end ownership across frontend, backend, data, and infrastructure, including real-time systems (Kafka/Postgres) and observability (Datadog). Built and productionized an AI-native RAG support assistant (OpenAI embeddings + Pinecone) with prompt/guardrail design, achieving 48% agent adoption and 30% faster responses. Experienced in legacy modernization and reliability work using feature flags, event/transaction replay, and rapid embedded delivery.”

“Built and shipped production LLM/RAG systems at Mayo Clinic, including a conversational AI assistant for patient pre-consultation and a clinical-trial matching tool for doctors. Implemented HIPAA-compliant de-identification and guardrails, plus real-time feedback logging and fine-tuning that improved response accuracy by 15% and reduced admin workload by 25%.”

Jayanti Lahoti

Screened

Junior Full-Stack Software Engineer specializing in AI and cloud-native systems

San Diego, USA2y exp

“Backend/systems-oriented engineer focused on building production-constrained LLM agent workflows that automate repetitive operator tasks via intent/entity extraction, retrieval grounding, and structured action recommendations with human-in-the-loop review. Emphasizes reliability through deterministic orchestration, strict tool/function schemas, observability, and disciplined evaluation/feedback loops, with strong experience handling messy multi-service operational data and idempotent execution.”