Vetted Flask Professionals

Harika M

Screened

Mid-level Full-Stack Developer specializing in FinTech and enterprise platforms

Plano, TX6y exp

“Engineer with a pragmatic, production-focused approach to AI-assisted development, using tools like Copilot and ChatGPT to accelerate coding while maintaining strict validation for correctness, security, and performance. Particularly notable for building a multi-agent incident-resolution workflow for a financial platform, with specialized agents for log analysis, root cause identification, fix suggestions, and test generation.”

“ML engineer at CGI who built demand forecasting models end-to-end, from feature engineering and training through AWS deployment. Stands out for a production-first mindset and strong skepticism of AI-generated code, including catching a Copilot-generated SQL query that would have caused a costly full table scan in production.”

Bhagyashree Patil

Screened

Intern Applied AI Engineer specializing in LLM systems and data engineering

Los Angeles, CA1y exp

“Full-stack engineer with hands-on production experience across both traditional SaaS and LLM-powered support tooling. They owned a real-time ecommerce order tracking dashboard that improved support response times by 40%, and helped ship an AI support assistant using the OpenAI GPT API that cut ticket handling time by 30% through strong prompt design, retrieval grounding, validation, and human-in-the-loop safeguards.”

Pallavi Hogalagere Anandareddy

Screened

Mid Software Engineer specializing in backend systems and FinTech

Tampa, FL4y exp

“Backend/full-stack engineer with experience spanning banking implementations at FIS and hands-on product building in React, TypeScript, Node.js, SQL, and Python. Stands out for owning six bank go-lives end-to-end, building an AI resume evaluator, and proactively automating manual operations workflows to reduce errors and improve consistency.”

“Backend-leaning full-stack engineer who has shipped both enterprise workflow software and AI-powered document intelligence products. Stands out for combining practical product judgment with strong production debugging skills across Spring Boot, GraphQL, FastAPI, vector search, and RAG systems, and for improving adoption by making AI search experiences intuitive for non-technical users.”

Raj Kalantri

Screened

Intern-level Software Engineer specializing in AI/ML and full-stack development

Kolkata, India1y exp

“Built a sophisticated AI career counselor as a full-stack web app for early-career students, integrating React, Flask, Pinecone, and LLM inference into a stateful conversational product. Stands out for combining hands-on debugging of retrieval/embedding pipelines with strong browser-performance instincts and pragmatic UX iteration based on real user testing.”

Joshua Newell

Screened

Senior Software Engineer specializing in embedded systems and secure communications

Remote, USA14y exp

“Engineer with experience in defense and aerospace-adjacent software, including serving as lead engineer on an SBIR contract for a Space Force warfighter communication system. Has hands-on full-stack experience improving a flight test sensor management application with React, Perl, and Oracle SQL, plus recent systems work in Rust observability and Go-based secure communications integration.”

Alex Guzman

Screened

Principal Software Engineer specializing in cloud infrastructure and identity systems

Denver, CO17y exp

“Senior backend-leaning engineer with experience spanning an 8-person early-stage startup and production microservices environments. They helped deliver an MVP for a fintech/charitable donations product by building a resilient abstraction API across multiple rewards vendors, and more recently maintained Go services at scale with Kubernetes autoscaling for workloads reaching roughly 1 million requests per day.”

Sri Teja

Screened

Mid-level AI Engineer specializing in LLM systems and enterprise data platforms

Phoenix, AZ5y exp

“Built and owned key parts of Ripley, an AI-powered multi-agent operations platform for roadside assistance that automates high-volume customer service workflows at production scale. They designed the orchestration, evaluation, monitoring, and enterprise integrations, helping drive 70-80% automation and ~99% reliability across thousands of weekly interactions and millions of annual requests.”

“Backend engineer who built and launched a warehouse locations/inventory microservice for Walmart, supporting a new product rollout with on-call war-room ownership and now running across all US distribution centers. Emphasizes reliability and correctness (background syncs, 2PC concepts, alerting) plus design-first API development in Python/FastAPI with OAuth/JWT and RBAC, and has led staged legacy-to-microservice migrations with continuous data integrity verification.”

“Backend/data platform engineer who has built and operated a cloud-native media ingestion/processing platform in Python (Django/DRF, FastAPI) with Kafka, Postgres, and Redis, emphasizing multi-tenant security and reliability. Delivered AWS production systems combining EKS and Lambda with Terraform + GitHub Actions/Helm, and built Glue-based ETL pipelines with strong schema-evolution and data-quality practices; also modernized SAS analytics into Python on AWS. Seeking fully remote roles with a $120K–$140K base range.”

“Backend engineer with hands-on experience modernizing high-volume transactional systems by decomposing monoliths into Spring Boot microservices on AWS, using Kafka for async workflows and Redis/SQL tuning for latency. Has built Python/FastAPI services with strong API contracts and production-grade security (OAuth2/JWT, RBAC, row-level security), and proactively hardened payment flows against race conditions and double-charging via idempotency.”

“Backend/data platform engineer who owned end-to-end production services for a fleet analytics/GenAI platform, spanning FastAPI microservices on Kubernetes and AWS (EKS + Lambda) event-driven workloads. Strong in reliability/observability (OpenTelemetry, circuit breakers, idempotency), data pipelines (Glue/Airflow/Snowflake), and measurable performance/cost wins (SQL 10s to <800ms P95; ~30% compute cost reduction).”

“GenAI engineer who has deployed production LLM/RAG chatbots for internal document search, focusing on reliability (hallucination reduction via prompt guardrails + retrieval filtering) and performance (latency improvements via caching). Experienced with LangChain/LangGraph orchestration for multi-step agent workflows and iterates using monitoring/logs and benchmark-driven evaluation while partnering closely with product and business teams.”

“GenAI/ML engineer with production experience at Cognizant and Ally Financial, building end-to-end LLM/RAG systems and ML pipelines. Delivered a domain chatbot trained from 90k tickets and 45k docs, improving intent accuracy (65%→83%), scaling to 800+ concurrent users with 99.2% uptime and sub-150ms latency, and driving +14% customer satisfaction. Strong in Azure ML + DevOps CI/CD, Dockerized deployments, and explainable/PII-safe modeling using SHAP/LIME to satisfy stakeholder trust and GDPR needs.”

“LLM/agent builder who has shipped production AI systems in the wellness space, including an LLM-powered food tracking product used by 5000+ users and a voice/call-routing onboarding workflow using LangGraph/LangChain with LiveKit and Twilio. Strong focus on practical reliability work: latency reduction, retrieval/embedding tuning, and CI-driven evaluation with simulations and metrics.”

“Software engineer with deep healthcare claims domain experience who has owned customer-facing portals end-to-end (Java/Spring Boot + React/TypeScript) and improved usability/performance based on real user feedback. Built microservices using REST and RabbitMQ with strong observability (Splunk/cloud metrics), and delivered an internal claims investigation dashboard that streamlined operations through centralized data, search, and filtering.”

“Software engineer with BitSight experience owning and revitalizing a critical internal Entity Management Portal (Django/React), clearing 30+ backlog items and boosting internal workflow efficiency ~40% through performance re-architecture (Redis caching) and disciplined testing. Also built a collaborative chore management platform (React/FastAPI) emphasizing responsiveness (optimistic UI) and scalability (connection pooling, Docker), and improved microservices security by centralizing secrets management with AWS Secrets Manager across multi-cloud environments.”

“Built a live free-to-play web-based financial market simulation game (YouTube-channel stock market) as a hobby project, now serving 3000+ users. Implemented core F2P systems including gacha, timed progression gates, and analytics-driven monitoring of engagement and economy health using a TypeScript/Python stack with Redis and Postgres.”

“Built a college AI chatbot during a master’s program, owning the full Python/Flask backend plus Google Gemini integration and a Postgres persistence layer (course info + conversation history), including caching/performance tuning. Also deployed and migrated ETL/ELT workloads from AWS Lambda into Kubernetes/EKS with GitHub Actions-based GitOps CI/CD, IRSA permissions, and Secrets Manager/S3/Postgres connectivity.”

“Backend engineer who built and optimized a high-traffic e-commerce platform in Python/Flask, focusing on scalability and reliability through service decomposition, Redis caching, and Celery-based background processing. Also integrated an AI intent-classification chatbot as a separately deployable inference service on AWS and has hands-on experience designing multi-tenant data isolation strategies in PostgreSQL.”

“Full-stack engineer who owned enterprise workflow platforms end-to-end at Northern Trust and Elevance Health—building NestJS/Java Spring Boot APIs, React UIs, and cloud deployments on GCP Cloud Run. Strong in data-heavy applications (hundreds of thousands of records) with proven production performance tuning (indexing/query rewrites, Cloud Run concurrency/min instances) and secure RBAC via Azure AD.”

“Backend engineer with hands-on ownership of FastAPI/Django services using MongoDB and React integration, focused on production reliability and performance (Redis caching, Celery background jobs, automated testing). Has delivered AWS container deployments via GitHub Actions to ECR with scripted rollouts/health checks, and supported phased migrations with replication and rollback planning. Also built a real-time user-activity streaming pipeline addressing partition hot spots and consumer lag through partition-key strategy, idempotency, and monitoring.”

“JavaScript/Node.js engineer with open-source contribution experience (Mongoose) focused on connection pooling, test reliability, and memory/resource management. Has diagnosed and fixed real-world performance issues in an insurance claims application and improved resilience via failover DB design. Also experienced producing compliance/governance documentation for an EU-based biopharma, enabling stakeholders to make decisions quickly amid changing regulations.”