Vetted Java Professionals

“Built and shipped an LLM-powered support assistant for a fintech payment reconciliation system that automated failed-transaction analysis at scale. Delivered measurable production outcomes (40% less manual reconciliation, 25% better detection accuracy, 99%+ uptime) and implemented strong reliability patterns (Prometheus/Grafana monitoring, retries/fallbacks, idempotency, Resilience4j circuit breakers) plus iterative retraining driven by real error analysis.”

Adam Safran

Screened

Engineering Director specializing in platform modernization, microservices, and cloud reliability

Pleasant Hill, CA26y exp

“Former founder (ran a custom web development shop in Los Angeles) with extensive startup experience and a solid working understanding of the VC ecosystem. Helped build and scale a team at Turo from founding member to ~10 people, and is motivated by ownership, impact, and originating ideas—interested in the venture studio model and disciplined about rapid validation and execution.”

Kishore Koduri

Screened

Director-level Enterprise Architecture leader specializing in AI and platform transformation

Akron, OH29y exp

“Entrepreneurial candidate with deep technology expertise who has already acted as a founder/principal across a real estate venture and early-stage tech startups. Most notably, they raised approximately $1-2M for a real estate project and describe hands-on ownership from ideation and business case development through ROI validation and investor commitment.”

“Full-stack web developer with experience owning products from client discovery through launch and post-launch iteration, including a complete freelance build for an interior design firm and a large-scale React/TypeScript migration during an internship at Gateway Ticketing Systems. Stands out for balancing strong visual design with performance and SEO, and for improving emergency-use UX in an MVP product through flow simplification and A/B testing.”

Keerthana Kondabathini

Screened

Mid-level Full-Stack Java Developer specializing in Healthcare IT and FinTech

4y exp

“Backend engineer with hands-on experience in both financial services and healthcare, including a Capital One credit application platform and an AI-assisted medical-records-to-EMR pipeline. Stands out for owning systems end-to-end, improving response times by 30%, operating services at 50K+ daily requests, and applying strong validation/observability practices in regulated environments.”

“Unity/C# game developer with hands-on experience shipping lightweight, analytics-driven gameplay systems across WebGL, multiplayer, VR, and mobile. Particularly notable for building a cloud-backed character builder with asset-bundle streaming and cross-device persistence, and for creating reusable level design tooling that improved design speed by 2.5x.”

“Backend engineer with strong payments and high-stakes transaction experience, including owning an Apple Pay/Google Pay integration via Stripe end-to-end in production for 100,000+ users. Particularly compelling for teams that need someone who can balance speed, security, and reliability in checkout or other sensitive backend workflows, and who has hands-on incident ownership in production.”

“Backend/ML engineer who built and operated a production WhatsApp assistant end-to-end using a modern RAG stack, delivering >90% automation with sub-2-second latency. Shows strong depth in retrieval quality, observability, evaluation, and incident handling, and has also applied similar AI workflow patterns to a clinical diagnostic assistant processing medical PDFs.”

“Currently at Berryble AI, this candidate is building an LLM-based real-time interview analysis engine using FastAPI, WebSockets, fine-tuned models, and GCP/Cloud Run. They stand out for using AI and agent workflows pragmatically to accelerate development while keeping human ownership over architecture, security, reliability, and maintainability, and they are also pursuing a master's in applied machine learning.”

“Data/ML engineer with end-to-end ownership experience at Charles Schwab, spanning data ingestion, anomaly detection, data quality infrastructure, and dashboards used daily by compliance and business teams. Stands out for debugging complex cross-layer issues in systems processing 17M+ records per day and for turning one-off data quality checks into reusable frameworks that scaled across business units.”

“ML/AI engineer with strong production depth across classical ML, MLOps, LLM/RAG, and scalable Python data platforms, with experience at Cisco and Accenture. Stands out for tying technical decisions to measurable business outcomes, including $1.2M annual savings, 40% faster support resolution, and broad internal adoption of shared engineering frameworks.”

Akhil Nakka

Screened

Mid-level Software Developer specializing in FinTech and cloud-native microservices

Remote, USA4y exp

“Full Stack Engineer in fintech (JPMorgan) who owns products end-to-end across React UIs and Spring Boot/Kafka backends, with a strong track record of shipping quickly while maintaining reliability via testing, monitoring, and feature flags. Has hands-on experience scaling microservices for high-volume transactions and debugging production latency using ELK/CloudWatch, plus built an internal Python/Flask automation tool adopted by backend engineers to speed API validation and debugging.”

“AI/ML engineer with production experience across both classical ML and Generative AI, including a real-time banking fraud detection platform at Deloitte and a RAG-based cybersecurity threat analysis feature at Accenture. Stands out for owning systems end-to-end—from feature pipelines and model tuning through deployment, monitoring, retraining, and API/platform reliability—with measurable impact on fraud accuracy, false positives, and SOC analyst efficiency.”

“Built production-scale dashboards and real-time data systems across fintech and autonomous driving, with hands-on ownership from React frontend architecture through Python/Kafka/Elasticsearch backend pipelines. At Zoox, led development of an automated safety signal attribution platform that replaced manual engineering calculations and surfaced trends through dashboards.”

Saumya Pailwan

Screened

Junior Software Engineer specializing in applied AI and audio ML

Evanston, IL2y exp

“Engineer with unusually mature experience leading AI-assisted development, including orchestrating multiple coding agents across a data pipeline feature as if managing a small engineering team. Stands out for balancing aggressive adoption of AI tools with disciplined judgment around architecture, security, and merge quality, and for translating that experience into stronger tech leadership.”

“Built and shipped a production LLM feature that converts natural-language search requests into Lucene queries for OpenSearch-backed device event data, improving usability for non-technical users. Brings hands-on experience across the full stack of agentic systems: model training, FastAPI/React integration, Kubernetes deployment on AWS, event-driven orchestration with NATS/Kafka, and production-grade evaluation/observability.”

“Hands-on engineering leader who has scaled teams quickly (hired 20 engineers in 4 months) and led major architecture shifts including monolith-to-microservices and serverless, async AI-driven medical data ingestion/search. Also drove a versioned-inventory redesign with auditability and rollback that reduced operational errors by 22%, and demonstrates strong incident response with clear stakeholder communication.”

“Revamped a university academic calendar system into a Python-based calendar generation service, turning a weeks-long manual scheduling workflow into software that generates dozens of valid calendar combinations in under a minute. Also contributed to an Amazon search ML classifier by introducing precision/recall evaluation to better surface critical failure modes and improve prediction quality.”

Vasudev Konde

Screened

Mid-level Full-Stack Java Developer specializing in APIs and cloud microservices

Phoenix, AZ5y exp

“AI/LLM engineer who has shipped a production document-intelligence agent that automated internal support workflows using RAG, tool calling, and robust fallback controls. Stands out for combining hands-on architecture with measurable business impact: 85% faster query resolution, 35% lower LLM cost, 40% fewer LLM calls, and enough automation to avoid adding 2-3 support engineers.”

Aaron Mcanerney

Screened

Mid-level Backend Software Engineer specializing in data platforms and reporting

Pleasanton, CA5y exp

“Built a production Medicare Q&A chatbot using OCR (pytesseract), LangChain chunking, ChromaDB embeddings/retrieval, and an Ollama LLM. Thinks in terms of practical tradeoffs (cost, model selection, static vs frequently-updated corpora) and emphasizes deterministic testing plus observability for reliable LLM workflows; also has experience automating non-technical teams' pain points (e.g., recruiting event integration).”

Prashant Singh

Screened

Mid-level Backend/Platform Engineer specializing in data pipelines, reliability, and AI-assisted ingestion

8y exp

“Backend engineer who built and scaled a blockchain-based e-voting platform at early-stage startup Elemential Labs, balancing decentralization with real-world operability by centralizing control-plane components while keeping the ledger immutable. Has hands-on experience migrating high-throughput ingestion from Kafka to AWS Kinesis with parallel cutover, strengthening data integrity and read-after-write consistency (Elasticsearch), and hardening pipelines against silent data-quality failures via anomaly detection and self-healing automation.”

“Builder/technical leader who was brought into Finicity to turn a credit-improvement concept into a viable product—architected, staffed, and launched what became Experian Boost. Delivered a major North American product launch in ~6 months, scaling to ~50,000 new users per day at launch and solving complex ML classification and distributed processing/order-of-operations challenges on AWS.”

“Full-stack engineer focused on high-throughput document/financial data platforms, building Angular/React front ends and Spring Boot microservices with Python/Flask services for heavy processing. Experienced in designing non-blocking, asynchronous workflows (Celery/RabbitMQ) and deploying containerized systems to AWS ECS with auto-scaling and CloudWatch monitoring.”

Kamal Virk

Screened

Senior Site Reliability Engineer specializing in cloud-native DevOps and Kubernetes

New City, NY13y exp

“IBM Power/AIX engineer with hands-on ownership of large AIX 7.1/7.2 environments (VIOS, HMC/vHMC) supporting enterprise middleware/back-end workloads. Demonstrated real production incident handling: identified CPU entitlement underprovisioning after a DLPAR change and restored performance via live CPU rebalancing, plus PowerHA failover execution and runbook/process hardening. Also builds secure CI/CD pipelines (Jenkins/GitLab/Azure DevOps with CyberArk) and Terraform IaC with drift management and controlled rollouts.”