Vetted Alerting Professionals

“Small-team builder of Promethium’s “Mantra” next-gen agentic text-to-SQL engine, using vector DB + LangGraph tooling and SQL validation/evaluation to improve query accuracy. Experienced in diagnosing production LLM workflow failures via LangSmith traces and in running hands-on developer workshops and pre-sales POCs with live debugging and real customer data.”

Daniel Jin

Screened

Intern Site Reliability Engineer specializing in Kubernetes, AWS, and observability

New York, NY1y exp

“Backend/data engineering candidate specializing in Python/Flask services and ML-enabled systems, deploying containerized workloads on AWS ECS/EKS with strong observability (Prometheus/Grafana) and PostgreSQL performance tuning. Built multi-tenant architectures with row- and schema-level isolation and optimized a Kubernetes-based Airflow + Spark nightly ETL pipeline for an e-commerce client, improving performance by 250%+ and reliably beating morning reporting deadlines; also contributed to Apache Airflow (SQLAlchemy/PostgreSQL area).”

Navindu Jayatilake

Screened

DevOps Technical Lead specializing in Kubernetes, AWS, and platform engineering

Colombo, Sri Lanka6y exp

“Sri Lanka–based DevOps/Platform engineer focused on Kubernetes and AWS who has led real production incidents and recoveries (network-policy-induced asymmetric routing; node pool failure due to CNI upgrade). Built production CI/CD with GitHub Actions (ephemeral self-hosted runners on EKS), ArgoCD, Vault, and Terraform, and led a phased ECS-to-EKS migration including Kafka consumers and MongoDB Atlas private endpoints.”

“Data engineer with Optum experience building end-to-end healthcare data pipelines for HL7/FHIR, processing millions of records daily across Kafka streaming and Databricks/Spark batch. Strong focus on data quality (schema enforcement/validations), reliability (Airflow monitoring/alerts), and analytics-ready serving in Snowflake powering Power BI/Tableau, with CI/CD via Git and Jenkins.”

“Backend/AI engineer who has owned production agentic systems end-to-end, including a CRM-integrated multi-agent financial workflow at Wow Payments that cut latency by 83% and achieved 98% uptime. Also built an AI real estate product ('Site IQ') by turning vague stakeholder goals into a geospatial autonomous agent using RAG, rapid prototyping, and tight validation layers around GPT-4 outputs.”

PrabhjyotKaur Bamrah

Screened

Mid-level Full-Stack Software Engineer specializing in enterprise apps and AI integration

Redwood City, CA4y exp

“Engineer with experience scaling enterprise AI products in production, including a C3 AI deployment expanded from 2 to 4 sites across the US and Canada. Also built a GPT-4o-powered RAG assistant for plant operators, combining structured and unstructured data with human-in-the-loop safeguards and iterative evals to improve answer quality.”

Supreet Purthpli

Screened

Mid-level Software Engineer specializing in FinTech and cloud-native systems

San Francisco, CA4y exp

“Software engineer with JPMorgan Chase experience delivering end-to-end fintech features (Next.js/React/Node/Postgres on AWS) and measurable performance gains. Built and productionized an AI-native credit decisioning workflow combining LLMs, vector retrieval, and a rules engine with strong governance (bias checks, auditability, human-in-loop), improving precision and cutting underwriting turnaround time by 40%.”

“Candidate indicated they live in New York but did not provide substantive details about their experience; they declined to discuss at least one topic as restricted and did not answer role-related questions with concrete examples.”

“Data engineer/backend data services practitioner with Bank of America experience building real-time and batch transaction-monitoring pipelines and APIs (Kafka + databases, REST/GraphQL). Highlights include a reported 45% response-time improvement through performance optimizations and use of Delta Lake schema evolution plus CI/CD (GitHub Actions/Jenkins) and operational reliability patterns like CloudWatch monitoring and dead-letter queues.”

“Data/ML platform engineer with healthcare (Cigna) experience owning an end-to-end pipeline spanning Airflow + Debezium CDC ingestion, PySpark/SQL transformations, rigorous data quality gates, and feature-store/API serving for ML training and inference. Worked at 10+ TB scale and cites a ~30% latency reduction plus stronger reliability via idempotent design, monitoring, and backfill-safe reprocessing; also built pragmatic early-stage data pipelines at Frankenbuild Ventures.”

“Data engineer/platform builder who has owned production pipelines end-to-end processing millions of records/day, with strong emphasis on data quality (quarantine workflows) and reliability (monitoring, retries, incremental loads). Also designed large-scale external data collection/crawling with anti-bot handling and backfills, and shipped versioned REST data services optimized for performance and developer usability in an early-stage environment.”

Niharika Bhasin

Screened

Intern Full-Stack Software Engineer specializing in AWS serverless and real-time web apps

New York City, NY0y exp

“New-grad/early-career engineer who led high-stakes modernization of a field-operations platform from Firebase to AWS using an incremental/dual-write strategy, achieving zero downtime and ~30–32% infra cost reduction while improving scalability. Also built and productionized an AI-native code assistant (LangChain + Pinecone RAG) with measurable online metrics and safety guardrails, and has experience working directly with CEO/CTO/CPO and embedded with customer teams to ship enterprise features quickly.”

“Former founding engineer and eventual CTO at 2Plus2 Partners (25 years ago) with additional experience in two private-equity-backed companies (apex analytix and HICX). Interested in helping build another company before retirement; comfortable with entrepreneurial risk but cannot self-fund significant capital.”

Rami Jaloudi

Screened

Senior Applications Engineer specializing in legal technology and eDiscovery

New York, NY16y exp

“Early-stage founder candidate exploring an AI-enabled legal tech startup focused on document intelligence, secure workflows, and enterprise automation. Brings a rare blend of technical architecture fluency and product/business thinking, with clear firsthand insight into legal and document-heavy operational pain points.”

“Pragmatic AI-focused builder who uses tools like ChatGPT and Claude to accelerate development while maintaining strict review, testing, and architectural ownership. Has hands-on experience designing lightweight multi-agent workflows, including a RAG-style system with separate retrieval and response roles, and approaches new AI trends through direct experimentation rather than hype.”

Arya Thorat

Screened

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

Texas, USA5y exp

“Full-stack/backend engineer with deep experience building real-time fraud and credit-risk systems. Shipped an event-driven fraud monitoring platform (Kafka→MongoDB/Redis→WebSockets) delivering sub-200ms updates to 3000+ concurrent internal users, and built a Java/Spring Boot credit risk decisioning API that improved turnaround time by 30–40%. Strong AWS production operations (ECS Fargate/RDS/Redis) with proven incident response and performance tuning.”

“Growth-stage startup engineer with strong end-to-end ownership across React, Java/Spring Boot, MySQL, and cloud deployment. They led workflow automation products that replaced manual operational processes, improved efficiency and reliability, and evolved the platform into a more configurable B2B workflow system shaped by user feedback.”

Rishabh Goyal

Screened

Mid-level Software Engineer specializing in backend microservices and FinTech

USA4y exp

“Python backend engineer focused on real-time e-commerce analytics systems, building FastAPI + Kafka microservices with strong idempotent processing patterns (Postgres upserts, manual offsets, Redis caching). Has hands-on Kubernetes (EKS) and GitOps delivery with Argo CD/GitHub Actions, plus experience migrating containerized services from on-prem VMs to AWS using Terraform and blue-green cutovers.”