Vetted Flask Professionals

“AI/ML engineer who shipped a production blood-test report understanding and personalized supplement recommendation product, using a LangGraph multi-agent pipeline on AWS serverless with OCR via Bedrock and RAG over vetted clinical research. Also built end-to-end recommender system pipelines at ASANTe using Airflow (ingestion, embeddings/features, training, registry, batch scoring/monitoring) with KPI reporting to Tableau, with a strong focus on safety, evaluation, and measurable reliability.”

“Backend/ML engineer who has built both enterprise data pipelines and real-time AI products: modular Python (Flask/FastAPI) services integrating automation scripts and low-latency ML inference (MediaPipe, PyTorch) plus OpenAI-powered feedback. Demonstrated measurable performance wins (~30% faster HR workflows; ~40% faster AWS pipelines across 100+ Oscar Health feeds) and strong multi-tenant/data-isolation patterns (schema-based isolation, RBAC, microservices).”

“Backend/data engineer with hands-on production experience building Python (FastAPI/Flask) data enrichment services secured with Okta OAuth2 and monitored via Splunk/Dynatrace. Has delivered AWS event-driven and data-migration solutions (Lambda + Kafka to EKS; Glue from on-prem Oracle to S3/data lake) and modernized Informatica match/merge logic to cloud services using parallel-run parity validation and stakeholder sign-off.”

“Software engineer with hands-on experience building data-intensive and 3D-processing web applications (React/Next.js/TypeScript + Node.js). Has worked in microservices using RabbitMQ for event-driven workflows and built an internal ops/engineering dashboard to monitor pipeline jobs, surface logs, and manage retries—improving visibility and reducing on-call/debug time.”

varsha viswanathan

Screened ReferencesStrong rec.

Entry-Level Software Engineer specializing in backend systems and FinTech

Fremont, CA1y exp

“Software engineering intern experience at Zoho Corp and Zeus Desk building and deploying customer-facing systems. Delivered a real-time booking platform backend that stayed stable for 1,000+ users by optimizing MySQL queries/indexing and shipping hotfixes during production latency incidents. Also integrated financial operations APIs across 50+ small-bank partners by creating a normalization/validation layer to handle inconsistent partner data and prevent integration breakages.”

Nidhi Sharma

Screened ReferencesStrong rec.

Junior Software Engineer specializing in backend systems, AI, and cloud infrastructure

Noida, India2y exp

“Built multiple AI-heavy systems with a strong engineering lens on observability, reliability, and real-world usability, including an LLM gateway for auditability/failure isolation and Allyvision, an accessibility tool for visually impaired users. Also owned an end-to-end warehouse shipment tracking dashboard at Addverb Technologies that drove measurable operational gains, combining backend/data depth with frontend product execution.”

Pranathi Kamisetty

Screened ReferencesStrong rec.

Intern AI Engineer specializing in LLMs, NLP, and conversational search

Chicago, Illinois1y exp

“Student building a production trip-planning LLM agent (LangChain + Streamlit) that routes user queries across multiple tools (maps/places/Wikipedia). Implemented zero-shot multi-label intent detection with priority rules to handle multi-intent requests, and collaborates with a startup product manager to shape tone, features, and user experience.”

Diya Wadhwani

Screened ReferencesStrong rec.

Mid-level Full-Stack Software Engineer specializing in MERN, AWS, and secure authentication

4y exp

“Application-layer full-stack engineer who has shipped enterprise-facing integrations and developer tooling, including an end-to-end Slack integration for automated ticket creation and a real-time feature-flag dashboard (React/TS + GraphQL/Apollo + NestJS) with audit trails. Has hands-on AWS container operations experience (ECS Fargate/ALB/RDS) and has improved product performance (35% faster dashboards) while building auth and RBAC for 500+ users.”

“Hands-on LLM/RAG engineer with production experience improving retrieval quality and stability by addressing messy data, vector DB inaccuracy, and top-K issues—ultimately redesigning to hybrid search with tuned keyword/semantic weighting and MCP-based data supplementation. Also brings strong AKS/Kubernetes deployment experience, optimizing CI/CD speed via lightweight local Docker validation and decomposing pods to avoid full rebuilds, plus a metrics-driven approach to agent/workflow testing and traceability.”

“Robotics software engineer with hands-on ROS (ROS 1) experience building sensor-processing and state-based control pipelines in Python/C++. Demonstrated measurable reliability and performance gains in autonomous navigation—cut runtime failures by 30%, reduced replanning by 35%, and improved debugging efficiency by 40%—using timing-aware state machines, message/interface discipline, and simulation/testing with Gazebo, rosbag, Docker, and CI/CD.”

“Full-stack web developer who reports owning both backend and frontend design, including database-first design and jQuery-based web UI work (shared a GitHub project link). Claims to have delivered a project planned for 4 months in just 2 weeks and emphasizes strong personal code quality standards.”

“Software engineer with a graphic design/marketing background who led a 4-month U.S. Department of State Diplomacy Lab project delivering a proprietary React/Electron + Flask + PostgreSQL scheduling app, including OKTA SSO integration under strict government confidentiality constraints. Also has hands-on production web experience fixing a broken WordPress/Elementor content system by scripting automated recategorization and date corrections.”

“Robotics software engineer focused on ROS 2 multi-robot coordination, having built task allocation and reliable inter-robot communication for simulated TurtleBot3 fleets. Demonstrates strong integration/debugging skills across Nav2 + gmapping (SLAM drift, TF tree, odometry/sensor fusion) and pairs it with production-minded tooling—Docker/Kubernetes deployments and CI/CD simulation testing via GitHub Actions.”

“AI Engineer at DXC Technology who has shipped production LLM/NLP systems on AWS (SageMaker, FastAPI) and optimized them for real-time latency and unpredictable traffic using quantization, batching, and autoscaling. Strong MLOps and monitoring discipline (MLflow, CloudWatch, SageMaker Model Monitor) and proven business impact—delivered models with 92% predictive accuracy and cut enterprise decision-making time by 30% through close collaboration with product managers.”

“Customer Success Engineer focused on secure customer integrations for web/AI analytics solutions, frequently aligning retail/business teams with security requirements. Has hands-on experience troubleshooting and hardening API-based integrations in AWS (IAM least privilege, VPC/private subnet patterns, CloudWatch/CloudTrail) and delivering repeatable containerized deployments via Bitbucket CI/CD.”

“End-to-end engineer focused on AI-native enterprise systems, including a production generative knowledge platform using RAG + semantic search over internal documentation (React, Python/Flask, GPU-hosted NLP models, Pinecone) with strong CI/CD and observability. Reports concrete outcomes including 40% faster knowledge access and ~75% employee adoption, and has led incremental cloud-native modernization using feature flags, parallel runs, canary releases, and regression testing.”

“Backend-focused Python engineer who owned high-traffic internal services end-to-end (FastAPI/Django) including REST/GraphQL APIs, PostgreSQL optimization, async task processing via SQS, and full CI/CD. Strong Kubernetes-on-EKS and GitOps (ArgoCD + Helm) experience, plus Kafka real-time streaming work and phased cloud-to-on-prem migration support.”

Anjana Priya Swathi Samudrala

Screened

Junior Full-Stack AI Developer specializing in LLMs and RAG applications

Orlando, US2y exp

“Product-minded software engineer who owned a Shopify POS app end-to-end at Swym, shipping an MVP and then scaling iteration speed with E2E automation and CI/CD—resulting in a Shopify Badge, Top-5 App Store ranking, and +40% new user acquisition. Also built an ESG insights tool using React/TypeScript + FastAPI with Snowflake and a RAG pipeline, plus microservices patterns (async jobs, queues, DLQs, autoscaling) and internal Metabase/SQL analytics dashboards.”

Isha Harne

Screened

Intern Software Engineer specializing in ML applications and LLM platform engineering

New York, NY1y exp

“Full-stack engineer who builds and scales customer-facing and internal AI products end-to-end (React/TypeScript/FastAPI/MongoDB) with strong product instrumentation and rapid MVP iteration. Built an AI-powered code review assistant adopted across teams and integrated into CI/CD, reducing manual review time by 30%+, and has hands-on experience with LLM retrieval/reasoning systems (LangChain + FAISS) and microservices scaling using RabbitMQ, Docker, and AWS.”

Pravelliika Chirivella

Screened

Mid-level Full-Stack Developer specializing in Django/React and FinTech automation

New York, NY3y exp

“Product-minded full-stack engineer who owns customer-facing products end-to-end and iterates quickly using MVP validation, feature flags, automated testing, and staged rollouts. Has built TypeScript/React systems with modular backends and designed microservices with async messaging (RabbitMQ), handling scale issues like ordering, retries, and idempotency. Also delivered an internal ops automation tool with a self-serve real-time workflow dashboard that reduced errors and drove rapid adoption.”

Tejas Belakavadi Kemparaju

Screened

Mid-Level Software Engineer specializing in backend, microservices, and ML systems

Newark, NJ3y exp

“Primary designer/implementer/maintainer of an open-source JavaScript library for programmatic SSML generation and validation in text-to-speech pipelines. Focused on safety-by-default APIs with vendor-specific extension adapters, strong backward compatibility/deprecation practices, and measurable performance gains by removing redundant validation stages. Emphasizes developer experience through example-driven documentation and systematic community issue triage.”