Vetted gRPC Professionals

Pre-screened and vetted.

HR

Mid-level Python Developer specializing in cloud-native FinTech platforms

Texas, USA4y exp
IntuitAvila University
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TS

Senior Full-Stack Developer specializing in cloud-native microservices (AWS)

Irving, TX8y exp
U.S. Bank
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MG

Executive trading systems architect specializing in fixed income and multi-asset platforms

Naples, FL25y exp
Outsetnet, LLC
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TW

Senior Machine Learning Engineer specializing in AI systems, LLMs, and MLOps

San Francisco, CA14y exp
SiftUniversity of Central Florida
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SL

Senior Software Engineer specializing in backend microservices and data platforms

Colorado Springs, CO12y exp
ZocdocUniversity of Minnesota
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Fatema Tuzzohra - Senior Full-Stack Java Developer specializing in banking and healthcare platforms in Hicksville, NY

Senior Full-Stack Java Developer specializing in banking and healthcare platforms

Hicksville, NY12y exp
U.S. BankKhulna Women's College

Enterprise-focused full-stack/backend engineer with hands-on experience shipping a production LLM-powered document analysis platform for internal operations teams. They combine cloud-native microservices expertise across AWS/Azure with practical agent-system design, including async orchestration, model routing, observability, and safeguards for hallucinations, failures, and human-review fallbacks.

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Nithin Reddy - Mid-Level Software Development Engineer specializing in distributed systems and event-driven architectures in Santa Clara, California

Nithin Reddy

Screened

Mid-Level Software Development Engineer specializing in distributed systems and event-driven architectures

Santa Clara, California4y exp
Goldman SachsCentral Michigan University

Built and maintained an internal JavaScript/React real-time event monitoring UI used by multiple Goldman Sachs teams (e.g., Private Wealth Management and Bulk Trading Systems). Focused on scaling performance under hundreds of events/sec—using profiling, memoization, batching, and debouncing—and paired it with strong internal documentation and disciplined incident diagnosis via synthetic load testing and logs/metrics.

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SA

Sharath Addepalli

Screened ReferencesStrong rec.

Mid-Level Software Engineer specializing in Python microservices and scalable web APIs

Franklin, TN3y exp
NissanUniversity of Florida

Backend engineer who replaced an Excel-heavy forecasting workflow with a secure, auditable FastAPI system (React UI + relational model + async workers), emphasizing deterministic processing, idempotency, and versioned ledger-style ingestion. Led a monolith-to-FastAPI migration at Bounteous using a strangler approach, feature-flagged incremental rollout, and data reconciliation/shadow-compare to protect integrity while scaling onboarding workflows.

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NG

Naga Gayatri Bandaru

Screened ReferencesModerate rec.

Mid-level AI/ML Engineer specializing in MLOps and production ML systems

Cleveland, Ohio3y exp
Cleveland ClinicSan José State University

Backend/ML engineer who has shipped high-scale real-time systems across e-commerce and healthcare: built a PharmEasy real-time recommendation engine for ~2M monthly users (cut feature latency 5 min→30 sec; +15% cross-sell) and architected a HIPAA-compliant multimodal clinical diagnostic workflow (DICOM+EHR) with XAI, MLOps (MLflow/Airflow/K8s), and drift/monitoring guardrails supporting 10k+ daily predictions.

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AM

Junior AI/ML Engineer specializing in anomaly detection and LLM/RAG systems

Fort Mill, SC2y exp
HoneywellNortheastern University

Built and productionized a tool-first, multi-agent framework that augments an anomaly detection model with domain context to generate trustworthy, evidence-backed anomaly explanations (including false-positive likelihood). Architected the platform to be model/orchestration/vectorDB agnostic (e.g., GPT + CrewAI + ChromaDB vs Claude + LangGraph + other vector DB) with strong performance, reliability, and OpenTelemetry-based observability. Also built a personal LangGraph-based "mock interviewer" agent that asynchronously fuses voice + live code input using state reducers, stop conditions, and fallback routing.

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SS

Sanjesh Singh

Screened

Mid-Level Software Engineer specializing in embedded RTOS and applied AI

Austin, TX3y exp
University of Texas at AustinUniversity of Texas at Austin

Master’s student and Deep Learning teaching assistant who teaches LLM/VLM fine-tuning (including LoRA) and built a Hugging Face LLM fine-tuned for unit conversion, improving reliability by analyzing synthetic data and filling missing number-system conversion examples. Also implemented the Raft consensus protocol using gRPC in a distributed systems course with correctness validated by unit tests.

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RP

Rubesh Phaiju

Screened

Senior Full-Stack Java Engineer specializing in cloud-native microservices and GenAI

Mechanicsburg, PA8y exp
DeloitteUniversity of the Cumberlands

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.

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AB

Ananya Bojja

Screened

Mid-level AI/ML Engineer specializing in healthcare analytics and MLOps

USA4y exp
CignaUniversity of New Hampshire

AI/ML engineer at Cigna Healthcare building a production, HIPAA-compliant LLM-powered clinical insights platform that summarizes unstructured medical notes using a fine-tuned transformer + RAG on AWS. Demonstrates strong end-to-end MLOps and cloud optimization (distillation, Spot/Lambda/Auto Scaling) with quantified outcomes (~28% accuracy lift, ~40% less manual review, ~25% lower ops cost) and strong clinician-facing explainability via SHAP and dashboards.

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SS

Shivam Sah

Screened

Mid-level Backend Software Engineer specializing in distributed microservices

New York, United States4y exp
ActiveViamNortheastern University

Internship at ActiveVM where they tackled large-scale Spring Boot 2→3/library migrations across hundreds of downstream products by combining OpenRewrite (AST-based recipes) with an LLM/RAG-based classifier that routed risky files to human experts. Reported ~70% reduction in manual effort and 90%+ accuracy after testing across multiple branches and cutovers; also built a CTR-driven book recommendation capstone showcased at the Google office in Cambridge.

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Gnaneswar Markat - Mid-level Software Engineer specializing in cloud-native distributed systems in Charlotte, NC

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

Charlotte, NC4y exp
Bank of AmericaUniversity at Buffalo

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.

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SR

Mid-level Generative AI Engineer specializing in LLMs and enterprise AI

Texas, USA5y exp
PNCUniversity of Texas at Arlington

Built and owned an enterprise LLM/RAG document intelligence platform for PNC Financial Services in a compliance-heavy environment, focused on grounded answers over internal finance and policy documents. Stands out for combining GenAI product delivery with production engineering discipline, delivering 60% faster document review and materially better answer quality while creating reusable FastAPI-based AI services for multiple teams.

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NA

Naiya Adatiya

Screened

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

Vermont, USA4y exp
Vermont Information ProcessingNortheastern University

Engineer with a process-driven approach to AI-assisted software development, focused on orchestrating where AI adds value while maintaining human review and verification. Has applied this in backend work such as an S3-based invoice pipeline and used multi-agent workflows to speed up large API refactors across many endpoints.

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VT

Mid-level AI/ML Engineer specializing in Generative AI and agentic systems

4y exp
WalmartUniversity of Central Missouri

Backend/platform engineer who has owned a Python/FastAPI results API and deployed it on Kubernetes with Helm and GitHub Actions-driven CI/CD. Demonstrates strong production operations mindset across performance tuning, monitoring, safe rollouts/rollbacks, and phased migrations, plus hands-on Kafka streaming experience focused on ordering and idempotency.

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Aditya Rao - Mid-level Software Engineer specializing in backend, AI, and distributed systems in San Jose, CA

Aditya Rao

Screened

Mid-level Software Engineer specializing in backend, AI, and distributed systems

San Jose, CA5y exp
Snap-onSan Jose State University

Software engineer with 4.5 years of startup experience across programmatic advertising, health tech e-commerce, and automobile diagnostics, plus both bachelor's and master's degrees in CSE. Built an agentic global supply chain platform in a hackathon using a highly structured AI-first workflow, and has hands-on experience designing multi-agent debate systems, rollout safeguards, and observability-driven production fixes.

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Yuanmu Li - Junior Software Engineer specializing in full-stack web applications in Sunnyvale, CA

Yuanmu Li

Screened

Junior Software Engineer specializing in full-stack web applications

Sunnyvale, CA2y exp
WalmartPenn State University

Full-stack product engineer in the health and wellness space who has owned prescription workflow features end to end, including React/TypeScript frontend work and GraphQL-backed API aggregation across messy downstream systems. Also shipped an internal OpenAI-powered support assistant with grounded context, structured outputs, validation, and human-in-the-loop safeguards—showing strong practical judgment at the intersection of healthcare workflows and applied AI.

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ET

Evan Teague

Screened

Senior Software Engineer specializing in backend and data platforms

Bethesda, MD10y exp
Spatial Data LogicUniversity of Virginia

Series A startup engineer with broad full-stack ownership across backend, data, and frontend, including a real-time ingestion platform that scaled to 10x higher daily volume without downtime while cutting latency from minutes to seconds. Brings strong fintech and B2B SaaS experience building auditable, high-throughput systems for analysts, operations, and compliance teams in regulated environments.

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