Vetted Asynchronous Processing Professionals

Manasa Pantra

Screened ReferencesStrong rec.

Junior Software Engineer specializing in AI, LLM systems, and full-stack development

Stony Brook, NY2y exp

“Product-focused full-stack engineer at startup (Zippy) who shipped a production multi-agent AI system for restaurant operations plus payments workflows. Built end-to-end: RAG grounded on a Notion knowledge base, structured function-calling task routing, FastAPI/JWT multi-tenant backend, and a polished React+TypeScript owner dashboard. Has real production incident experience (duplicate Stripe webhooks) and reports ~94% task-routing accuracy under load.”

“Robotics software engineer/researcher focused on perception, SLAM, and sensor fusion, with hands-on experience taking systems from simulation to embedded/real-time deployment. Led transparent-surface (glass) detection using GDNet and achieved a major real-time speedup (~7–9 FPS to ~30 FPS) while preserving >90% recall, and has built ROS-based EKF GPS-IMU fusion plus profiled/optimized Visual SLAM for performance and memory stability. Also brings production-style deployment skills via Docker/Kubernetes orchestration of ML inference services with autoscaling and model update rollouts.”

“Full-stack engineer who built and owned an internal analytics dashboard for sales (React/TypeScript + Node/Express + NoSQL), delivering it two weeks early with zero production issues and a reported 10% sales-efficiency lift. Experienced with microservices and async messaging patterns (retries/DLQs/idempotency), and emphasizes rapid iteration with strong CI/CD and automated testing plus user-driven adoption.”

“Robotics-focused engineer from a senior capstone who built the backend motion-control software for a semi-autonomous line-following vehicle split across two ESP32s. Experienced in ROS 2 (DDS, lifecycle nodes, QoS) and in bridging microcontroller telemetry to a laptop ROS 2 stack over UART with custom structured protocols, using Gazebo simulation to tune PID and validate behavior before deploying to hardware.”

“Built a production RAG-based “unified assistant” that consolidates siloed company documents into a single chatbot while enforcing fine-grained access control via RBAC/metadata filtering with OAuth2/JWT. Experienced orchestrating LLM workflows with LangChain/LangGraph + FastAPI (async + caching) and measuring performance via retrieval accuracy and response-time SLAs. Also delivered a churn analytics solution with dashboards and automated retention campaigns using n8n.”

“Deloitte engineer who built and shipped AI-powered, Kafka-driven workflow automation for transportation/document processing, including LLM-based semantic search. Strong in production reliability (idempotency, offset management, retries), observability (Datadog/CloudWatch), and database performance tuning (PostgreSQL/Flyway), with measurable latency improvements.”

“Engineer with production experience in both high-throughput banking risk systems and LLM agent platforms. Built a real-time transaction risk scoring middleware at JPMorgan Chase (1M+ requests/day) emphasizing HA, observability, and audit/PII compliance, and also architected multi-step LLM agents with strict schema-based tool calling, evaluation loops, and safety guardrails for messy enterprise data.”

Arjun Masadi

Screened

Mid-level Full-Stack Developer specializing in cloud-native FinTech and Healthcare platforms

Remote, USA3y exp

“Full-stack engineer (3+ years) who owned an AI-powered customer financial health dashboard end-to-end at Regions Bank, combining React/Java Spring Boot with LangChain + Pinecone for personalized insights. Strong production operations experience on AWS EKS with CI/CD and observability (OpenTelemetry/Prometheus/Grafana), delivering measurable outcomes including 22% support reduction and 99.9% uptime, plus robust third-party financial/clinical integrations.”

Gnaneswar Markat

Screened

Mid-level Software Engineer specializing in cloud-native distributed systems

Charlotte, NC4y exp

“Full-stack engineer with Bank of America experience building and owning a customer portfolio dashboard end-to-end, from requirements through launch and ongoing iteration. They combine React/Spring Boot/PostgreSQL implementation with strong performance tuning, real-time data handling, and UX improvements, and cite adoption by roughly 12,000 active internal users.”

“Built Nexthire-AI, shipping an end-to-end LLM-powered resume–job description matching product (React + Node.js) using embeddings and retrieval to generate match scores and skill-gap recommendations. Improved post-launch engagement by making feedback cleaner and more actionable, and added production guardrails (validation, timeouts, fallbacks) to handle messy resume formats and AI API instability.”

“Backend/platform engineer who has built and scaled production Java/Spring Boot + Kafka services on AWS/Kubernetes (1M+ msgs/day) and led reliability/performance fixes that restored SLAs (25–30% latency improvement; 99.9% uptime). Also shipped an AI customer-support chatbot end-to-end using retrieval + guardrails and rigorous evaluation/observability, improving resolution time 40% and satisfaction 25%, with a strong plan/execute/verify approach to agentic workflow reliability.”

“Backend/data engineer with hands-on production experience across Python REST APIs and PostgreSQL, plus AWS containerized deployments using CloudFormation, Jenkins CI/CD, and CloudWatch monitoring/autoscaling. Has built data validation/ETL-style workflows with schema/version checks and targeted reprocessing, modernized legacy batch processing into Java services with phased parallel migrations, and delivered measurable SQL performance gains (~50% query runtime reduction).”

Harshini Jaligama

Screened

Senior Full-Stack Java Developer specializing in cloud-native microservices and FinTech

Remote, USA5y exp

“Full-stack engineer (5+ years with Java/Spring Boot and React) who has built and deployed AWS-based microservices platforms using Kafka for real-time rewards/promotions and large-scale telemetry analytics. Demonstrates hands-on scalability expertise (partitioning, consumer groups, durability/acks, idempotency) and production-minded delivery practices (CI/CD, Docker, testing, Swagger, monitoring).”

Jaideep bommidi

Screened

Senior ML Engineer & Data Scientist specializing in LLM agents, retrieval/ranking, and MLOps

Denton, TX8y exp

“Machine Learning Engineer currently at Webster Bank building an enterprise-scale LLM agent for Temenos Journey Manager/Maestro, using RAG-style multi-stage retrieval with FAISS/Pinecone, hybrid dense+sparse search, and LoRA fine-tuning optimized via NDCG/MAP and A/B testing. Previously handled messy incident/telemetry data at Deuta Werke GmbH with deterministic + fuzzy entity resolution, and has strong production data engineering experience across Spark/Hadoop and Python ETL systems.”

Bryan West

Screened

Senior Software Engineer specializing in AI, cloud infrastructure, and full-stack development

Chantilly, VA17y exp

“ML/NLP engineer who built a production system that converts large-scale unstructured text into a connected, searchable knowledge base using spaCy + Sentence Transformers/FAISS and a Neo4j knowledge graph, with BERTopic and XGBoost for organization/labeling. Strong focus on production-grade Python workflows (FastAPI/Celery, Pydantic validation, Docker, AWS ECS/Lambda) and robust entity resolution with measurable precision/recall and human review for low-confidence matches.”

Goutami Amara

Screened

Mid-level Full-Stack Java Developer specializing in FinTech and Healthcare platforms

Memphis, TN6y exp

“Software engineer who built internal operations/monitoring dashboards for real-time trading and money-movement systems, emphasizing auditability and rapid iteration. Deep experience with microservices on Azure using Kafka/RabbitMQ, plus strong testing discipline (JUnit/Mockito/Testcontainers, contract/E2E) and observability patterns (correlation IDs, centralized logging, distributed tracing) to reduce incident triage time and improve resilience.”

Sai Vamsi

Screened

Mid-Level Software Engineer specializing in backend microservices and cloud-native systems

TX, USA4y exp

“ServiceNow engineer who built an AI-powered ticket summarizer end-to-end (RAG with vector DB + GPT, Redis latency optimizations, fallback summarization, and a React UI widget for agent feedback). Also has hands-on ROS 2 experience building real-time sensor-fusion nodes (LiDAR/IMU), debugging SLAM/navigation issues via rosbag + EKF tuning, and bridging heterogeneous robots by translating ROS 2 topics to MQTT/JSON. Strong DevOps background with Docker, Jenkins CI/CD, and Kubernetes orchestration for scalable deployments.”

Jeetendra Girish Vasisht

Screened

Junior Software Engineer specializing in cloud-native microservices

Bangalore, India2y exp

“Backend engineer (Nokia) who designs and migrates cloud-native microservices at scale, including a secure low-latency system handling 500k+ daily transactions. Strong in Kubernetes/OpenShift operations, CI/CD standardization, and production security (OAuth2/JWT/RBAC) with SOC2-aligned controls and zero critical security incidents. Demonstrated expertise in safe migrations (canary/blue-green, dual writes, reconciliation) and concurrency correctness in real-time systems.”

“Candidate brings a pragmatic, production-focused approach to AI-assisted software development, using AI as a pair programmer and conceptually applying multi-agent workflows across coding, testing, and review. They stand out for putting strong guardrails around AI usage—manual review, testing, SonarQube, peer review, and keeping critical logic manual—to improve speed without compromising security or code quality.”

Ravindrareddy B

Screened

Junior Full-Stack Java Developer specializing in enterprise web applications

Ames, IA2y exp

“Full-stack engineer with hands-on experience building an internal telecom order-tracking/dashboard platform at T-Mobile across React, Spring Boot, and PostgreSQL. Stands out for owning features end-to-end, from scalable frontend architecture and TypeScript patterns to API design, query optimization, CI/CD, and post-launch monitoring in AWS CloudWatch.”

Jessy Kattupalli

Screened

Mid-level Full-Stack Java Developer specializing in enterprise web applications

West Haven, CT4y exp

“Backend engineer who built and scaled a transaction-processing microservice (150K+ records/day) in a microservices ecosystem, debugging peak-load latency/timeouts via CloudWatch/Grafana, Kafka lag analysis, and DB query tuning (indexes, Redis caching, batching). Also shipped an LLM-powered document assistant end-to-end with prompt/response validation plus retries/fallbacks for production reliability.”

“Built and shipped a production multi-agent conversational AI platform (Monitor agent + RAG + 4 additional agents) with enterprise REST APIs, using ChromaDB-grounded WCAG knowledge to keep responses accurate while varying tone via personality modes and conversation memory. Has experience at LinkedIn delivering technical demos and pre-sales guidance to both engineering teams and C-level stakeholders, acting as a translator between sales and technical teams to drive adoption.”

“Backend-focused Python/Flask engineer with strong performance and scalability experience across PostgreSQL/SQLAlchemy optimization, caching, and async processing. Has implemented multi-tenant data isolation (schema/db per tenant with RBAC and encryption) and integrated TensorFlow-based ML inference behind a Flask REST API using Redis caching, batching, and async execution; reports measurable wins like cutting endpoints from 6–8s to ~2s and increasing throughput 3–4x via Celery queues.”

“Built and shipped production systems spanning real-time operational dashboards and an LLM-powered internal documentation assistant using RAG (embeddings + vector DB). Demonstrates strong focus on reliability and iteration: implemented guardrails and evaluation loops (human review, hallucination tracking, regression prevention) and improved performance/scalability through query optimization, caching, and retrieval tuning.”