Vetted Observability Professionals

“Engineering leader who has operated effectively in both a VC-backed startup and SAP, combining director-level org leadership with day-to-day technical depth. Notable for re-architecting integrations that produced a 3x revenue gain, leading a 90-engineer matrixed organization, and staying hands-on in GenAI, infrastructure, and full-stack problem solving.”

Krishna Guda

Screened

Principal Software Engineer specializing in AI-native FinTech systems

Mountain View, CA23y exp

“Fintech product engineer working on a large-scale credit monitoring platform (tens of millions of users) with deep experience in regulated banking integrations, PII security, and step-up/MFA flows. Has shipped customer-facing React/TypeScript experiences driven by Optimizely experimentation and built reliable partner-facing microservices/SDKs on AWS, including resolving production traffic loss caused by edge security (DataDome/CAPTCHA) conflicts with payment providers.”

“Front-end/UI engineer who built and standardized a complex metadata component system for 2,500+ banking users across 40+ internal product surfaces. Stands out for combining design-system architecture, browser-level CSS expertise, and workflow-sensitive UX for demanding financial users, including a token system that resolved 488 style references and a reusable responsive component library adopted across five product areas.”

“Healthcare IT engineer with deep observability, backend, and database expertise who built mission-critical monitoring solutions across major enterprise transitions including Siemens, Cerner, and Oracle. Stood out by creating a DoD-deployed observability platform for 10,000+ HL7 interfaces and by automating hospital financial day-end workflows, cutting issues by 90% and freeing up 14 FTEs.”

Amulya Varshney

Screened

Mid-level Software Engineer specializing in Applied AI and FinTech

Bangalore, India3y exp

“Built and shipped production AI systems in high-stakes domains including fintech at Razorpay and payroll at Intuit. Most notably owned Ray, an AI-powered merchant support concierge that automated about 70% of support tickets and cut response times from hours to seconds, combining full-stack product work with LangGraph-based agent orchestration, RAG, and rigorous evaluation infrastructure.”

“Java full-stack developer who has owned data-intensive, customer-facing and internal web products end-to-end (React/Angular + Spring Boot), including CI/CD and production support. Demonstrates deep microservices experience with RabbitMQ/event-driven architecture, idempotency, DLQs, and compensating logic to maintain reliability and data consistency at scale, plus a track record of replacing spreadsheet-based ops reporting with an adopted real-time internal tool.”

“Backend/platform engineer building HIPAA-compliant, real-time healthcare systems: owned a Python/Flask API layer for an AI-enabled patient engagement and risk scoring service, implemented PHI-safe logging and cross-service auditability, and delivered Kubernetes microservices via ArgoCD GitOps. Also has experience with Kafka streaming pipelines and hybrid cloud-to-on-prem migrations in regulated healthcare/fintech environments.”

“LLM/MLOps engineer who has shipped production systems for complaint intelligence and contact-center NLU, including LoRA/RLHF-tuned LLaMA models deployed on GKE with vLLM and Vertex AI batch pipelines to BigQuery. Demonstrates strong practical focus on hallucination control, data imbalance mitigation, and production monitoring (Langfuse) with regression testing and canary rollouts, plus experience orchestrating complex workflows with AWS Step Functions.”

“Built and shipped a production LLM-powered RAG assistant for enterprise internal document search (PDFs, knowledge bases, structured data), addressing real-world issues like noisy documents, hallucinations, and latency with grounded prompting, retrieval-confidence fallbacks, and performance optimizations. Also partnered with compliance and business teams at JPMc to deliver a solution aligned with regulatory constraints, supported by monitoring, feedback loops, and systematic evaluation.”

“AI/ML engineer (Cognizant) who built a production, real-time credit card fraud detection platform combining deep-learning anomaly detection with an LLM-based explanation layer. Strong focus on regulated deployment: addressed class imbalance and feature drift, and added guardrails (SHAP/structured inputs, fine-tuning on analyst reports, rule-based validation) to keep explanations accurate and compliant. Orchestrated the full pipeline with Airflow + Databricks/Spark and used MLflow/Prometheus plus A/B and shadow deployments for measurable reliability.”

“Backend-focused full-stack engineer who built an MVP at Neon AI for PhD students: a FastAPI backend integrating multiple cloud and local LLMs plus a RAG pipeline with session/identity management, designed to be modular and extensible across domains. Also has VMware experience debugging production issues and executing safe, API-compatible refactors with staged rollouts and strong security controls.”

“AI/full-stack engineer with experience delivering production-critical healthcare AI at Roche (digital pathology imaging platform using Microsoft Gigapath for cancer diagnosis) and building scalable LLM-backed products. Strong in designing async AI backends (Django/Celery/Postgres/Redis on GCP), reliability engineering (Datadog, incident response), and agent-style document analysis workflows with evaluation loops.”

Manaswini Gogineni

Screened

Junior Software Engineer specializing in cloud infrastructure and full-stack web development

San Francisco, CA2y exp

“Full-stack/platform engineer who has owned real-time analytics products end-to-end and built scalable TypeScript/React + Node.js systems using event-driven and microservices architectures (Kafka/RabbitMQ). Also created a widely adopted Go CLI that standardized AWS/Terraform provisioning across multiple teams, cutting environment setup from days to minutes through opinionated defaults, documentation, and cross-org partnerships.”

Sakshi Dinesh Deore

Screened

Mid-level Software Engineer specializing in AWS, DevOps automation, and data platforms

Bellevue, USA3y exp

“Engineer with Securonix experience deploying and operating production microservices and real-time data-processing systems at high throughput. Led AWS infrastructure, CI/CD, monitoring, and customer-driven customization for a threat-report classification solution, including rule adjustments and model retraining based on live client feedback.”

“Backend/data platform engineer who owned a production merchant-activity aggregation and event publishing system processing ~500k merchants daily. Built a Snowflake-based daily KPI summarization pipeline orchestrated via AWS Glue/SQS and an ECS Spring Boot publisher that encrypts and publishes events to Kafka, with strong operational monitoring and reconciliation. Drove major scalability wins (10x throughput) via caching around encryption/key-management and designed selective reprocessing to handle late-arriving data cost-effectively.”

“Backend/data-systems SWE (2 years) who has built production ETL/streaming workflows (Kafka, Debezium, Elasticsearch) and troubleshot real SQL performance regressions caused by indexing/type issues. Also ships full-stack personal projects in Next.js App Router + TypeScript with Postgres, emphasizing reliability via constraints, idempotency, and strong observability (Grafana/Kibana).”

“Backend/microservices engineer with fintech loan-lifecycle experience operating low-latency (sub-250ms) services in production using Kafka, idempotent transaction design, and Datadog observability. Also built an end-to-end LLM chatbot (React + Flask) with a decoupled model integration layer (FLAN-T5 via Hugging Face) and has experience designing partner-facing REST APIs with OAuth2/JWT and Swagger documentation.”

Nicholas Moore

Screened

Senior Full-Stack Engineer specializing in scalable cloud-native systems

Lehi, Utah13y exp

“Backend/data engineer with production experience building high-concurrency customer engagement platforms at KomBea on AWS (EKS + Lambda) using FastAPI/Django, PostgreSQL, Redis, and strong observability. Has modernized legacy batch systems into modular Python services with parallel-run parity validation and phased rollouts, and has delivered resilient AWS Glue ETL pipelines with schema evolution and data quality controls.”

Eric Low

Screened

Principal Engineering Leader specializing in platform, product, and AI advisory

14y exp

“Fractional CTO/lead engineer who shipped an end-to-end Next.js + FastAPI product experience (login, data processing results, chatbot Q&A) with an architecture designed to support future ML model integration. Has led large-scale engineering enablement (continuous delivery across ~150 devs/200 systems), owned production incident response with lasting test/contract improvements, and delivered a 3x productivity gain by fixing debugging/tooling bottlenecks while mentoring junior teams into independent delivery.”

Yash Nileshkumar Mirani

Screened

Mid-level Software Engineer specializing in AI agents, data pipelines, and cloud systems

Sunnyvale, CA5y exp

“Generalist software engineer with recent contract work at Vertex Pharmaceuticals shipping a desktop-integrated RAG assistant for lab scientists (2000+ pages ingested; ~40% support-ticket reduction in pilot). Previously owned Python/AWS financial automation services at Amazon operating at multi-billion-dollar scale, with strong strengths in API design, observability, and database/performance tuning; also built a React/TypeScript AI contract analysis product (ContractsGuy).”

“Platform/infrastructure-focused engineer with hands-on experience automating AWS EKS upgrades in Python, building observability around logs/metrics/SLOs, and migrating Terraform delivery from CodePipeline to Atlantis. They describe shipping automation that handled 140 resources across 50+ Terraform files ahead of schedule and debugging a Karpenter/CoreDNS regression in Kubernetes by tracing it from regional traffic spikes to a missing local DNS cache configuration.”

Mustafa Ali

Screened

Mid-level Software Engineer specializing in backend systems and AI

Boston, MA4y exp

“Founding/early backend engineer at ATICA Global who built the company's core hotel property management platform from an empty repo into a production system used by 500+ hotel clients. Combines strong backend architecture with pragmatic product execution, including a dynamic pricing engine that increased partner revenue 17% YoY and an AI-powered sentiment pipeline processing 200K+ reviews/month.”

“Senior engineering leader with over 20 years of management experience and a hands-on background leading large-scale SaaS, eCommerce, CRM, and customer data platform systems serving millions of users. Stands out for combining deep technical architecture leadership with org-scale people management, including solving multi-tenant SaaS scaling issues, driving self-service product improvements from support patterns, and building governance models for cross-functional delivery.”

“Engineering leader focused on multi-cloud platform modernization, combining deep hands-on expertise in Kubernetes, Terraform, GitOps, and DevSecOps with management of 18-person DevOps/SRE/software teams. Particularly strong in building secure, scalable enterprise SaaS infrastructure and Spark/Databricks data platforms while driving cross-functional standardization, reliability, and faster release cycles.”