Vetted Confluence Professionals

“Financial-services AI engineer who shipped a production investment research assistant using RAG over internal research reports, SEC filings, and meeting transcripts, with a strong emphasis on truthfulness and guardrails. Built a structured evaluation loop (200+ golden test cases, RAG Triad metrics) that directly improved retrieval quality (e.g., fixing year-mismatch retrieval, boosting sensitive-query performance by 18% and cutting hallucinations to near zero) and scaled ingestion to ~10k messy documents with RabbitMQ + OpenTelemetry.”

“Full-stack engineer with production experience building a security integrations portal in Next.js (App Router + TypeScript), using server components and typed route handlers as a secure proxy to multiple third-party security vendors. Demonstrated ability to scale performance significantly (server-side re-architecture for 1M+ datapoint dashboard filtering; Postgres query tuning from 1–2s to <200ms) and to own features post-launch (reliability, caching/background sync, and rapid onboarding of new integrations) in a pre-Series B through post-Series C environment.”

Srinivas Matta

Screened

Mid-Level Full-Stack Software Developer specializing in cloud-native web platforms

Paducah, KY4y exp

“Software engineer at Capital One who owned and shipped AI-driven personalization and internal insights dashboards end-to-end, emphasizing fast iteration with feature flags and tight user feedback loops. Built a TypeScript/React + Spring Boot/Python document automation platform with compute-heavy NLP microservices, async workflows, and production-scale reliability/performance practices (Kafka/RabbitMQ-style queues, Redis caching, tracing).”

Sayali Patil

Screened

Mid-level Python Full-Stack Developer specializing in Healthcare and FinTech

Everett, MA6y exp

“Backend engineer with hands-on experience building a fraud-transaction monitoring system in Python/Flask, architected as Dockerized microservices and integrated with Kafka for high-volume streaming. Demonstrates strong performance and reliability chops across PostgreSQL/SQLAlchemy tuning (EXPLAIN ANALYZE, N+1 fixes, bulk ops), multi-tenant data isolation, and scaling via background workers + Redis caching, plus real-time ML inference deployment using TensorFlow on AWS.”

Naga Manasa Bandaru

Screened

Mid-level Frontend Software Engineer specializing in React, Next.js, and TypeScript

Dallas – Fort Worth, TX4y exp

“Product-focused full-stack engineer with FedEx experience building an internal logistics dashboard for near real-time shipment status and performance metrics using Next.js App Router + TypeScript. Strong in production ownership and performance work—uses React Profiler/Chrome DevTools to eliminate expensive re-renders and applies Postgres indexing/query tuning validated via EXPLAIN ANALYZE to improve dashboard responsiveness.”

Sankalp Tiwari

Screened

Mid-Level Software Engineer specializing in backend microservices and FinTech data pipelines

New York, NY4y exp

“Backend engineer at Goldman Sachs who built LLM-powered reconciliation/reporting services and high-throughput Kafka pipelines (8M+ events/day). Strong in production-grade Python/FastAPI microservices on Kubernetes with GitOps-style CI/CD, plus experience migrating legacy reporting/settlement services onto an internal Kubernetes platform using shadow deployments and gradual cutovers.”

“Analytics candidate with hands-on experience at BCBS building HIPAA-compliant SQL/Snowflake/Tableau pipelines across fragmented legacy healthcare systems. Stands out for turning a 5-day claims reporting process into a near real-time 10-minute dashboard and for pairing strong data engineering discipline with reproducible Python-based churn modeling that drove measurable retention outcomes.”

“Analytics-focused candidate with strong SQL, Excel, Python, and Tableau skills who supports payroll-, compensation-, and finance-adjacent processes through rigorous data validation and reconciliation. Stands out for uncovering a duplicate-record mapping issue that exposed roughly $250K in revenue leakage and for building repeatable controls, dashboards, and automated checks to improve reporting accuracy.”

“Built and owned Alight's AI-powered Search Summary feature end-to-end, using a RAG pipeline with OpenSearch and Bedrock, and drove a 20% increase in user feedback scores. Stands out for bringing rigorous production evaluation to LLM systems via live LLM-as-a-judge monitoring, and for experience with advanced agentic architectures, hybrid search, and reranking at scale.”

Fumin Sun

Screened

Junior Product Analyst specializing in AI-driven FinTech analytics

New York, NY2y exp

“Analytics-focused candidate from Street Diligence who has built operational reporting and product/engagement metrics from messy platform, Jira, and manual-log data. Stands out for turning unreliable manual processes into trusted, repeatable SQL/Python workflows that influenced staffing, weekly targets, renewal prep, and a product matching-logic fix.”

Benjamin Feldman

Screened

Director-level application development leader specializing in FinTech and digital transformation

Boston, MA16y exp

“Hands-on engineering leader in a private-company/startup-like environment who builds full-stack financial systems and leads small teams. Notably replaced a failed third-party banking platform with an in-house Azure-based product integrating major bank APIs, driving $200K-$300K in annual savings and major workflow automation and performance gains.”

“Product-minded full-stack engineer with experience shipping engagement features and core communication systems at DribbleUp and Expys. Stands out for combining rapid MVP execution with rigorous iteration: delivered a leaderboard feature that lifted engagement by 8% initially and 20% overall, built a chat MVP in 3 days, and has hands-on experience deploying LangChain-based concierge agents with evals and human review.”

“Senior business analyst/project manager with broad enterprise implementation experience across multiple business functions and platforms, including ERP, custom web apps, AI chatbot deployment, and ITSM asset migration. Stands out for owning projects end-to-end, using iterative requirements workshops and visual process mapping, and finding practical configuration workarounds when out-of-the-box systems fall short.”

“Senior product leader with experience across Times Internet, Mudah.my, Wells Fargo, and delivery/logistics products, spanning SaaS, marketplace, fintech, and AI-enabled platforms. Stands out for building products end-to-end with strong commercial outcomes, including a multi-channel engagement platform that became a new SaaS revenue stream and AI features that improved marketplace liquidity while keeping humans in control.”

“Sourcing/procurement professional with end-to-end ownership of vendor selection, negotiation, and delivery for AI-enabled workflow automation products. Uses structured scorecards, SLA/KPI-driven supplier management, and dual-sourcing strategies to reduce risk—delivering measurable outcomes like 18% cost savings, OTD improvement from 82% to 96%, and 25% rework reduction while navigating data quality drift and trade/duty exposure.”

“Platform-focused engineer/technical program leader working in silicon/wafer validation environments, with hands-on experience securing access to sensitive test results and engineering tooling. Has implemented RBAC/least-privilege controls with Azure Entra ID, Key Vault, PAM and integrated Checkmarx into dev workflows, while also deploying ML services on AKS using Bicep/Helm/Docker and Azure DevOps CI/CD with strong monitoring and incident response practices.”

“Built a production internal RAG-based Q&A assistant at Huawei for ~4,000 engineers over a 12M-document Elasticsearch corpus, replacing link-only search with synthesized answers and achieving 87% user acceptance while keeping hallucinations under 0.4%. Pairs rigorous offline benchmarking (RAGAS, PR-gated F1 improvements) with human A/B testing and OpenTelemetry-based production monitoring, and also has strong Kubernetes/SRE experience orchestrating 50+ gRPC services with major MTTR and pager-fatigue reductions.”

“Full-stack engineer with strong DevOps/AWS production experience who builds and operates multi-agent AI systems end-to-end (Streamlit/Python through Docker/Kubernetes and ECS/Fargate). Has delivered measurable outcomes: sub-2s latency and ~92% routing accuracy for an AI wellness assistant, shipped an AI-for-BI prototype in under 6 weeks cutting analysis time ~40%, and improved pipeline iteration speed ~35% via modularization and CI/regression checks.”

“Game QA professional with live production experience owning QA strategy for a cross-platform seasonal loadout system in a live server shooter. Works in Agile/Scrum with CI/CD, using Jira + TestRail (including two-way sync) to drive traceable test coverage and fast triage via evidence-rich bug reports. Emphasizes risk-based coverage, regression discipline across builds, and converting gameplay feel into actionable design/engineering feedback.”

“Software engineer with hands-on experience building a distributed ticketing system on AWS (Terraform, Go, MySQL) focused on high-concurrency reliability (locks/queues to prevent duplicate ticket confirmations) and load-tested performance. Also independently owned and shipped an Airflow automation script to stop/restart workflows during deployments with email notifications, reducing manual operational effort.”

“Full-stack engineer with fintech/trading domain experience (Fidelity) and startup SaaS CRM/billing platform work (Zoho), building real-time portfolio analytics and trade-processing systems. Strong in microservices, event-driven architectures (Kafka/WebSockets), and AWS/Kubernetes operations with measurable performance gains (~34–35% latency reduction) and maintainability improvements (~40% faster deployments). Targeting a founding full-stack engineer role in NYC with meaningful equity.”

Pavan Kumar Malasani

Screened

Mid-level AI/ML Engineer specializing in financial risk, fraud detection, and GenAI

Remote, USA4y exp

“GenAI/ML engineer in Citigroup’s finance environment who has deployed production RAG systems for investment banking under strict privacy and model-risk constraints. Built an internal-VPC Llama2 + Pinecone + LangChain solution with NER redaction and citation-based verification to prevent hallucinations, delivering major time savings, and also partnered with global finance executives to ship an AI early-warning indicator for treasury/liquidity risk.”

“Healthcare data engineer with hands-on ownership of claims/member data pipelines on a cloud analytics platform, spanning batch and streaming ingestion (Airflow/Kafka/Spark/Databricks) through serving for reporting. Emphasizes reliability and data quality via embedded validation, schema-drift detection, deduplication, and operational monitoring/incident response, plus pragmatic CI/CD and observability setup in early-stage/ambiguous projects.”

CLEVELAND DEAR

Screened

Senior Game Designer specializing in systems, progression, live ops, and AI

Austin, TX13y exp

“Level designer/gameplay systems designer who shipped on Squid Game Unleashed, taking ownership of bot navigation and a dynamic bot-profile system to keep matches flowing and bots feeling human via telemetry-driven tuning (Tableau/heatmaps). Also built a lightweight minigame variant/rules framework to rapidly ship fresh live-service content with minimal engineering/art overhead, and has live-ops economy/event design experience from MyVegas Bingo.”