Vetted Alerting Professionals

“Backend-leaning full-stack engineer in lending/financial services (Kotak Mahindra Bank Autos360; currently at Ally Financial) working on Spring Boot microservices with React dashboards. Has built reliability improvements for credit-bureau integrations (Experian) and created an internal monitoring/reporting platform that aggregates metrics/logs/ETL across services, cutting troubleshooting by ~40%.”

“Backend engineer who built an e-commerce order processing service in Python/Flask with PostgreSQL, focusing on correctness and reliability (idempotency, Redis locks, async payment processing with circuit breakers). Also integrated an ML recommendation system as a separate FastAPI inference service with caching and async embedding updates, reporting ~25% CTR lift, and has experience with multi-tenant isolation using PostgreSQL row-level security.”

“Backend engineer who has delivered large, measurable performance wins (10x throughput, 67% latency reduction) by combining Flask microservices, Redis caching, and AWS autoscaling/observability. Has hands-on depth in SQLAlchemy/Postgres optimization and production scaling pitfalls (cache consistency, connection exhaustion), plus experience deploying real-time ML inference (XGBoost) on AWS Lambda and building secure multi-tenant Kubernetes isolation.”

“Built and shipped a production LLM-powered internal operations automation platform using LangChain RAG (Pinecone) and FastAPI microservices, deployed on AWS EKS, serving 10k+ daily interactions. Implemented a rigorous evaluation/observability stack (golden datasets, prompt regression tests, MLflow, retrieval metrics, hallucination monitoring) that drove hallucinations below 2% and improved reliability, and partnered closely with non-technical ops leaders to cut manual lookup work by 60%+.”

Mike Khorrami

Screened

Director-level Engineering Leader specializing in enterprise SaaS and cloud-native platforms

Woodland Hills, CA25y exp

“Engineering leader/player-coach who modernized a legacy C#/SQL Server system to Snowflake + Python on GCP, enabling ~30x scale and supporting hundreds of millions of transactions per day per customer. Strong in architecture tradeoffs (Snowflake vs Databricks), production reliability (New Relic, logging/alerting), and lightweight process improvements like a rigorous Definition of Done and structured PR reviews.”

Harshitha Parupalli

Screened

Mid-level Data Engineer specializing in multi-cloud real-time and batch data pipelines

Jersey City, NJ4y exp

“Data engineer with healthcare domain experience who owned 100M+ record pipelines end-to-end (Kafka/Kinesis/ADF → PySpark/dbt validation → Spark SQL transforms → Snowflake/Power BI serving). Built production-grade reliability practices (Airflow orchestration, CloudWatch/Grafana monitoring, pytest + contract/regression tests, idempotent ingestion/backfills) and delivered measurable improvements: 35% lower latency and 40% better query performance.”

“SRE-oriented infrastructure engineer who built an internal Vertex AI/Gemini knowledge chatbot to centralize product and development documentation, cutting routine support questions from 10+ daily to roughly 2. Also brings hands-on experience debugging Kubernetes production incidents and monitoring ETL/data-quality issues in Dataflow-based pipelines.”

“Backend/AI infrastructure engineer focused on production-ready LLM systems and distributed workflows. They described building a RAG-based multi-step agent with strong reliability controls, evaluation loops, and graceful degradation that improved latency by 30%, retrieval accuracy by 15%, and reduced support workload by 40%.”

Rutuja Sanjay Risbood

Screened

Senior Full-Stack Software Developer specializing in enterprise web and mobile applications

San Jose, CA8y exp

“Front-end engineer with unusually deep browser-systems knowledge, having built and owned a real-time merchant analytics platform for financial analysts handling millions of live transactions. Stands out for combining low-level performance engineering, typed React architecture, and expert-user UX polish, with strong measurable outcomes across speed, usability, and maintainability.”

“Healthcare product leader who started as a front-end engineer/unofficial product head and helped transform a custom hospital software business into a SaaS platform that became the company's flagship, generating over 80% of revenue. Later, as VP of Product after acquisition by Press Ganey, they led multi-product consolidation across global teams and launched HIPAA-compliant genAI features that delivered measurable customer efficiency gains.”

“Backend/platform engineer from Dune Security with strong experience turning messy, fragmented workflows into reusable production systems. They’ve built a shared database abstraction layer, integrated multiple enterprise security platforms into a unified workflow, and shipped AWS Bedrock-powered security insight features with guardrails and human review.”

“Backend/AI engineer who has shipped an LLM-powered enterprise support-ticket agent at Comcast, building a production-grade microservices pipeline (FastAPI, SQS, Redis) with strong observability (OpenTelemetry/Splunk/Prometheus/Grafana) and reliability patterns (async, caching, circuit breakers, idempotency). Demonstrated quantified impact at scale—processing 10k+ tickets/day while improving response SLAs and routing accuracy through evaluation and human feedback loops.”

“Built and shipped an internal Financial Insights Assistant for banking analysts, owning the experience from workflow design through React frontend, FastAPI backend, and AI search integration. Particularly strong in making AI products usable and trustworthy by surfacing sources, experts, suggested prompts, and search history to improve confidence and speed.”

“Backend/distributed-systems engineer (Amazon; also Bank of America) pivoting into robotics software. Built and owned an end-to-end cross-region event processing service for Aurora Global Databases, emphasizing correctness under latency/clock skew, fault tolerance, and strong observability; brings deep Docker/Kubernetes and CI/CD experience to robotics infrastructure and reliability work while ramping up on ROS 2.”

“Embodied AI / robotics-focused ML engineer with experience at JPMorgan and EY building language-to-robot control systems that connect transformer/LLM intent to safe real-world robotic actions. Designed production-grade, low-latency architectures (Kafka/Redis, monitoring, CI/CD) and applied sim-to-real and model distillation to make research ideas deployable on physical systems.”

“Hands-on engineering manager/lead focused on Azure application deployments and CI/CD automation. Has led design sessions and 1:1 code reviews, and owned a production performance incident end-to-end from measurement and test-environment setup through production validation, while coaching team members via regular 1:1s.”

“Data/MLOps engineer (Cognizant background) who owned an AWS/Airflow/Snowflake healthcare transactions pipeline processing ~8–10M records/day and cut pipeline/data-quality incidents by ~33%. Also built and deployed a production FastAPI model-inference service on Kubernetes (Docker, HPA) with strong observability (Prometheus/Grafana), versioned endpoints, and resilient backfill/idempotent external data ingestion patterns.”

“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.”

“Backend/data engineer focused on AWS-based, event-driven systems—building Golang microservices and serverless pipelines with strong data validation, observability (CloudWatch/Splunk/New Relic), and reliability patterns (retries/DLQs). Has also operated distributed web scraping/data collection with schema versioning and Step Functions backfills, and ships well-documented, versioned REST/WebSocket APIs for internal and external consumers.”

“Engineer working on high-throughput financial systems who uses AI pragmatically to accelerate development without sacrificing design ownership, correctness, or compliance. Particularly interesting for teams building regulated, real-time platforms: they have hands-on experience integrating fraud detection models into microservices, handling transaction ingestion, scoring, decisioning, and throughput-sensitive asynchronous workflows.”

“Backend-leaning full-stack engineer who has shipped real-time, customer-facing dashboards and ticketing/payment features at Freshworks and Global Payments. Strong in Python API design (Django/Flask/FastAPI) and React/TypeScript UIs, with hands-on experience scaling PostgreSQL for high transaction volumes and operating services on AWS, including incident response and HIPAA-aligned security controls.”

“Java/Spring Boot engineer with startup-style ownership experience across e-commerce, banking, and healthcare analytics. Stands out for driving a monolith-to-microservices migration with Kafka that improved checkout reliability under peak load, while also contributing full-stack with Angular and supporting production operations end to end.”

“Frontend engineer with experience at US Bank and S&P Global building complex React dashboards for analysts working with real-time, high-volume transaction and model-performance data. Stands out for combining performance tuning, scalable state architecture, and usability improvements that directly reduced manual analysis effort for expert users.”

“Software engineer with experience at Walmart and Amex building customer-facing backend services and microservices at scale (RabbitMQ). Built an internal developer tooling platform integrating Figma with GitHub Copilot to automate consistent React component creation, adopted across multiple teams; emphasizes fast, safe iteration using metrics, feature flags, gradual rollouts, and automated testing.”