Vetted Go Professionals

Vagmin Yadav

Screened

Junior Software Engineer specializing in backend systems, ML pipelines, and DevOps

Pune, India2y exp

“TypeScript backend engineer in the robotics domain with hands-on experience building low-latency (20–40ms) production systems using RabbitMQ, Redis, and HA PostgreSQL (Patroni). Has owned end-to-end services supporting 15 clients via config-driven architecture, with strong CI/CD, automated testing, and observability (OpenTelemetry) practices, plus API versioning/deprecation using Keycloak auth.”

Anandapadmanabhan Santhosh

Screened

Junior Software Engineer specializing in distributed systems and backend microservices

Bangalore, India1y exp

“Distributed systems engineer (ex-Nykaa, Licious) who built a PBFT-based Byzantine fault-tolerant consensus system in Go for a multi-node banking-style application, including checkpointing and automated failover/leader election. Strong production reliability background with Docker, Jenkins CI/CD, and monitoring/on-call troubleshooting using Grafana and New Relic; no direct ROS/robotics hardware experience yet but has highly transferable multi-node coordination expertise.”

“Built Baioniq, an enterprise LLM platform for automating extraction from massive unstructured documents like contracts and insurance claims. They demonstrate unusually strong production depth in agentic AI—scaling to 100k+ requests/day, processing 1M+ claim documents, and improving extraction accuracy through rigorous RAG architecture, evaluation, and fallback design.”

“Built and owned a production conversational AI platform for a healthcare contact center, including RAG-based agent assist, hybrid retrieval, safety guardrails, and production monitoring. Stands out for combining LLM product delivery with strong operational rigor, driving a reported 25-30% improvement in handling time in a sensitive healthcare environment.”

“Built and launched a production self-healing MLOps agent that autonomously diagnosed and fixed model training failures on Kubernetes GPU infrastructure. Combines deep AI infrastructure knowledge with full-stack product ownership, and has delivered measurable impact including 35% less infrastructure waste, nearly 50% less troubleshooting time, and 60% lower LLM API costs.”

“Architecture leader from Disney who managed system, AI, and data architects while staying hands-on in solution design. Has experience building LLM-based video advertising products, designing Kafka-based real-time data architectures, and using MVP/POC approaches to align product and executive stakeholders.”

“Engineer working in a venture-studio-style company that spins up SaaS products and new businesses, often owning early product and technical direction across teams ranging from 1 to 100 people. Particularly strong at hardware-software systems: they led software design and hardware choices for a 360 vision product and built a company-wide HIL testing platform with Go/Python/TypeScript, multi-language SDKs, and flexible endpoint architecture.”

Adam Sandler

Screened

Senior Full-Stack Engineer specializing in Python web platforms

7y exp

“Full-stack engineer with strong Python and React/TypeScript experience who has worked in lean startup environments on B2B SaaS hiring platforms. Most notably, they drove redesign work on developer search and matching systems at G2i, combining product collaboration, backend architecture, and database/query optimization to improve match quality and keep search responses around 100ms at scale.”

“Full-stack engineer with hands-on ownership of a customer-facing advanced performance metrics experience in the Amazon S3 console, spanning React UI, Python/Node services, Redshift/RDS data access, and AWS IaC/CI-CD with CloudWatch/Route53 operational readiness. Demonstrates strong production instincts around resilience (partial failures, multi-region inconsistencies), progressive rollouts/feature flags, and reliable ETL/integration patterns (idempotency, backfills, reconciliation).”

Ranfei Pang

Screened

Mid-level Software Engineer specializing in AI systems and FinTech

Boston, MA4y exp

“Amazon warehouse-tools engineer with strong full-stack and GenAI systems experience, spanning large-scale provisioning platforms and internal LLM/chatbot products. They’ve owned systems end to end, including React/TypeScript frontends, Java/AWS backend orchestration, and Bedrock-based RAG architectures, with measurable impact on latency, token cost, validation quality, and operational support load.”

“Backend engineer with production experience on an AWS Lambda-based payment service (manually deployed) and hands-on modernization work using parallel-run + diffing to prove parity before cutover. Has practical production troubleshooting experience for batch/pipeline incidents using monitoring/logs and emphasizes idempotent rerunnable jobs for safe recovery; also improved GraphQL performance by refactoring overly broad queries.”

“Built a production-style PyTorch LSTM system that generates structured piano compositions from 1200+ MIDI files, then significantly improved long-range musical coherence by implementing Bahdanau attention based on research literature. Also has internship experience using Docker Compose for containerized backend workloads and has independently used Ray to scale ML experiments across multiple GPUs, including dealing with GPU scheduling/memory oversubscription issues.”

“Solutions Engineer focused on application and platform security for enterprise cloud-native deployments, advising customers on threat modeling and secure CI/CD practices across AWS and Kubernetes. Has implemented SCA/container scanning and vuln checks in pipelines, tuned thresholds to reduce false positives, and driven outcomes like faster security approvals and smoother production rollouts. Troubleshot high-load Kubernetes failures (OOMKills, registry throttling) and turned fixes into a standard tuning guide.”

“Backend/platform engineer with experience across edtech, logistics, and AWS internal systems—owned a production course recommender end-to-end (model serving + APIs + caching/observability), delivering +30% CTR and -20% latency. Has scaled real-time delivery visibility/rerouting on Kubernetes/EKS to sub-200ms P95 during demand spikes and built billion-events/day telemetry pipelines on AWS (Kinesis Firehose, Lambda, S3, Redshift) with schema evolution, dedupe, and replay support.”

“Infrastructure/DevOps engineer with primary ownership in enterprise Linux and AWS/Azure production environments (including financial systems). Built secure, repeatable CI/CD pipelines deploying containerized workloads to EKS/ECS and implemented Terraform/CloudFormation IaC with drift detection and rollback practices; lacks direct IBM Power/AIX/PowerHA experience.”

Deepika Gotla

Screened

Senior Technical Support Engineer specializing in Azure Cloud & Generative AI

Bellevue, WA7y exp

“Microsoft cloud/infra engineer with 5+ years supporting enterprise Azure environments, specializing in security-focused networking (private endpoints, DNS) and production troubleshooting across Azure Front Door/App Gateway WAF/AKS. Has implemented posture improvements via Defender for Cloud, Azure Policy, and RBAC tightening, and also designs secure AWS agent/scanner integrations and modern EKS/GitHub Actions/Secrets Manager observability-enabled SDK rollouts.”

Shobana Chandrasekaran

Screened

Mid-Level Software Engineer specializing in AI microservices and generative fashion

Sunnyvale, CA2y exp

“Backend/AI workflow engineer at a startup building production AI services for fashion workflows, including an AI-powered techpack generation API in Go (Gin) with MongoDB handling ~1k+ daily requests. Recently implementing an image-to-3D dress generation feature end-to-end, integrating a Python FastAPI AI service with ComfyUI + Hunyuan, with strong emphasis on async orchestration, webhooks, and observability (OpenTelemetry + SigNoz).”

Blake Thomas

Screened

Director-level Engineering Leader specializing in AI and EdTech platforms

San Mateo, CA21y exp

“Has been on the receiving end of a VC investment and took responsibility for significant parts of the diligence process, drawing parallels to hands-on work with security compliance and auditors. Approaches entrepreneurship and idea selection with a structured framework (leverage, resources/runway, passion) and a sustainability-first mindset around risk and personal/family well-being.”

Parth Tusham

Screened

Intern Software Engineer specializing in systems, cloud, and security

Sunnyvale, CA1y exp

“Systems and infrastructure engineer pivoting toward robotics software; brings strong low-level debugging, multithreaded systems, and networking experience where correctness and timing matter. Has hands-on experience using Docker and CI/CD to build reproducible test/evaluation environments (thesis), and proposes a disciplined, contract-driven approach to distributed communication and real-time performance debugging.”

Shyaam Sundhar Rajamadam Srinivasan

Screened

Director-level Cybersecurity Architect specializing in cloud security, threat detection and incident response

Reston, VA18y exp

“Entrepreneur building an AI-enabled platform to help tradespeople (e.g., plumbers/carpenters) find customers, currently moving from ideation toward MVP and user launch. Previously founded Votimo (2012), an early philanthropy/donation-transparency platform, raised ~ $2M in angel funding, and implemented the system before strategic drift from leadership/vision changes.”

“Data engineer with experience at Expedia building SQL Server and Azure Data Factory pipelines for business reporting and analytics. Stands out for pragmatic end-to-end pipeline ownership in ambiguous environments, with a strong emphasis on data quality, rerunnability, query performance, and making downstream datasets reliable for other teams.”

“Built Multipass at Gemini, a Flask/React system that provisioned AWS access across 98 accounts for 400+ engineers, with a strong focus on reliability, observability, and hardening brittle auth flows. Earlier at Deloitte, turned a Word-doc HR onboarding SOP for CVS Health into 45 Workday integrations using XML/XSLT, cutting manual work by 38% and improving data accuracy by 12%.”

“Product-minded software engineer with experience shipping AI-powered financial insights (spend forecasting, cashflow, credit optimization) and building real-time analytics systems using React/TypeScript and FastAPI. Has designed microservices with RabbitMQ/gRPC and strong observability (Prometheus/Grafana/OpenTelemetry), and also built an internal Figma plugin adopted by designers that reduced export time by 50%.”

“Full-stack engineer from early-stage startups who has owned AI products end to end, from B2B document intelligence platforms on AWS to an HVAC voice assistant and a GCP-based RAG research system. Stands out for combining hands-on backend/infra depth with team leadership in lean environments, and for shipping scalable AI systems that contributed to roughly 1 million yuan in sponsorship.”