Vetted SQL Professionals

“AI/ML engineer who has shipped both a safety-critical mental health RAG chatbot (Mistral 7B + Pinecone) with automated faithfulness/toxicity monitoring and a deep Q-learning investment recommendation engine at Lincoln Financial Group. Strong in production MLOps and orchestration (AWS Lambda/CloudWatch/SageMaker, Docker, AKS) and in translating regulated-domain requirements (clinical reliability, fiduciary duty) into measurable model constraints and monitoring.”

“Built and shipped a production multi-agent, voice-based conversational assistant for older adults’ daily health management using Vertex AI, FastAPI, Firebase/Firestore, and Cloud Run, with a custom cross-session memory design to keep responses context-aware at low latency. Also partnered with caregivers/elderly users and health officials, translating needs into workflows and explaining HIV risk predictions with SHAP and dashboards.”

“AI engineer at Anote.ai who built and shipped a production multi-agent LangGraph/LangChain/Ray RAG platform for enterprise search and workflow automation, supporting 3 commercial products and 100+ developers. Drove measurable gains (30% accuracy improvement, lower latency) and improved reliability with Redis-based state checkpointing, message-queue synchronization, and Milvus retrieval optimizations, while partnering with PMs/clients to add transparency features like confidence scores and real-time logs.”

“Active in the venture ecosystem as a Rogue Women's Fund fellow and angel investor, with memberships in Gaingels and Angel Squad (HustleFund). Interested in founding a company to leverage extensive experience, and evaluates ideas through market need and economic viability of the target population.”

“Data engineer at Plaid who built greenfield, end-to-end real-time transaction pipelines and FastAPI data services for fraud detection and analytics, handling millions of events per day. Strong focus on reliability and data integrity via Great Expectations validation, Airflow-based monitoring/SLAs, quarantine/staging patterns, and robust external data ingestion with schema versioning and backfills (reported 50% fewer anomalies and ~40% fewer failures).”

Pranav Puranik

Screened

Senior AI Engineer specializing in LLMs, RAG, and multimodal NLP

Austin, TX5y exp

“Built a production LLM/RAG assistant for insurance/health claims agents that ingests 100–200 page patient PDFs via OCR (migrated from local Tesseract to Azure Document Intelligence) and delivers grounded claim detail retrieval plus summaries with PII/PHI guardrails. Experienced orchestrating large workflows with Celery worker pipelines and AWS Step Functions (S3-triggered, Fargate-based batch inference/accuracy aggregation), and collaborates closely with non-technical SMEs (claims agents/nurses) through shadowing, iterative demos, and SME-defined evaluation.”

Akhilaa Sonduri

Screened

Junior Full-Stack Software Engineer specializing in SaaS and AI-powered web apps

Cambridge, MA2y exp

“Full-stack engineer with experience at HubSpot, Accolite, and an early-stage USC alumni startup (Workup). Built and shipped end-to-end workflow automation features (dynamic input configuration with strict schema validation) driving ~25% faster configuration, and delivered an AI interview customization feature in a high-ambiguity startup setting that increased adoption by ~40%. Comfortable operating production systems on AWS with CloudWatch observability and CI/CD, and has built real-time web apps with caching/indexing for performance.”

Feras Alsaiari

Screened

Senior Software Engineer specializing in AWS data platforms and event-driven systems

4y exp

“Capital One engineer leading the architecture and delivery of a large-scale AWS Glue/Spark/Delta Lake batch messaging pipeline that decoupled batch from real-time flows, added multi-region failover and automated retries, and delivered ~40% AWS cost savings with ~3x performance gains. Currently building an LLM-powered Slack bot using RAG to automate message investigations by querying CloudWatch, Snowflake, and internal documentation with privacy-aware masking of NPI/PII.”

Changhee Lee

Screened

Mid-level Software Engineer and Product Manager specializing in AI and financial data platforms

Remote4y exp

“Full-stack engineer with deep Next.js App Router + TypeScript experience who has shipped and owned production features in a fashion/wardrobe/resale domain. Demonstrated measurable impact across the stack: +25% engagement, 30% faster load times, 40% fewer errors, plus durable Temporal workflows and Postgres analytics/query tuning for real-time dashboards.”

Rojin Bakhti

Screened

Junior Software Engineer specializing in Edge AI and ML deployment

San Diego, CA3y exp

“Qualcomm engineer building Android applications that run on Qualcomm AI accelerators, with hands-on experience in C++ concurrency, chipset stress testing, and power/performance tuning. Has deployed on-device AI models and built deployment/log post-processing workflows using Docker/Kubernetes and CI/CD; interested in translating this embedded AI/performance background into robotics (perception/real-time systems).”

Rahul Konala

Screened

Senior Strategy Consultant specializing in AI, SaaS, and TMT

New York, New York6y exp

“Cross-functional operator/program leader with experience running end-to-end platform and governance assessments and translating findings into OKRs and annual roadmaps. Central contributor to a large post-merger integration overseeing 15+ functions and identifying ~$55M in cost reallocation opportunities through headcount, process, and technology optimization.”

“Built and architected ML-integrated payment processing systems for PlayStation at Sony Interactive Entertainment, covering fraud determination, provider routing optimization, and model-training feedback loops in production. Brings a strong reliability and observability mindset, with concrete experience designing fallbacks, retries, correlation-ID tracing, and statistically grounded evaluation for non-deterministic systems.”

“Senior engineering leader from IBM who has built and scaled enterprise AI/GenAI platforms across hybrid and multi-cloud environments, combining executive-level org leadership with hands-on debugging of production distributed systems. Particularly compelling for Director/VP roles needing someone who can unify architecture, platform strategy, and engineering execution across multiple teams.”

Polat Akbiyik

Screened

Mid-level Software Engineer specializing in FinTech and trading systems

Remote4y exp

“Full-stack builder with strong product and AI systems ownership, spanning data infrastructure, React/TypeScript apps, and LLM-powered agents. Particularly notable for building a crypto analytics MVP with catalog-driven ETL, config-based charting, and AI-generated dashboards, plus an options-strategy agent and an ops automation tool that cut a 10-minute workflow down to 10 seconds.”

Jyothi Kumar

Screened

Senior Software Engineer specializing in full-stack enterprise SaaS and digital marketing

Mountain View, CA10y exp

“Atlassian engineer who grew from frontend into full-stack ownership, spanning React/TypeScript UI architecture, backend data pipelines, observability, and Kotlin/Spring Boot integrations. They describe owning Confluence profile-service integration tied to signup growth, plus building a marketing analytics platform with caching, reusable components, and data-quality tooling that increased stakeholder adoption by 30%.”

“Staff-level engineer with a track record of building greenfield, high-impact platforms inside major enterprises like Apple TV, CAA, and Disney. Particularly compelling for teams that need startup-style ownership with enterprise-grade execution: they’ve driven cross-department adoption, built AI and real-time systems hands-on, and delivered measurable operational gains in media, content, and ERP environments.”

“Senior full-stack engineer with seed-stage fintech experience who has led payment API development, implemented compliance-related standards, and built production systems across React, Go, Python, Node.js, and PostgreSQL. Notable impact includes enabling a first major client launch, reducing logistics response times by 30%, improving page load times by 40%+, and cutting analytics report generation from minutes to seconds.”

Shanay Wadhwani

Screened

Mid-level Data Scientist specializing in NLP, computer vision, and applied ML

Washington, DC6y exp

“AI/ML engineer with impactful work for the World Bank across both LLM systems and computer vision, including a PRAI evaluator-assistance platform and a production UNet model for slum detection from multispectral satellite imagery. Earlier built multilingual NLP-based borrower segmentation and credit scoring at Creditmate through its acquisition by Paytm, showing strong experience in ambiguous, high-impact environments.”

“Data engineer/backend developer with experience owning end-to-end, high-volume data pipelines for ML/analytics using Python, Airflow, SQL, and PySpark, reporting ~30% error reduction through improved reliability and data quality checks. Has also built Django-based REST APIs with caching/pagination and strong versioning practices, and operated external data collection/web scraping pipelines with anti-bot measures, monitoring, retries, and idempotent backfills.”

“Full-stack engineer with strong AI systems and B2B SaaS experience across BrightOps, Zapier, Nordstrom, and Calendly. They’ve owned architecture for an AI-powered tutoring platform, improved retrieval quality with a hybrid vector-plus-keyword approach, and built Go services processing over 1 million student events per day. Particularly compelling for teams building data-intensive, reliability-critical products with LLM, workflow automation, or compliance-oriented use cases.”

“Built and shipped customer-facing AI systems in banking, including an AI fraud support workflow and virtual assistant at Citi/Citibank that handled over 1 million conversations per month. Combines full-stack engineering, LLM/RAG architecture, and strong compliance-minded design with PII masking, audit logging, confidence thresholds, and human escalation for regulated environments.”

“Product-minded software engineer with experience shipping AI-powered financial insights (spend forecasting, cashflow, credit optimization) and building real-time analytics systems using React/TypeScript and FastAPI. Has designed microservices with RabbitMQ/gRPC and strong observability (Prometheus/Grafana/OpenTelemetry), and also built an internal Figma plugin adopted by designers that reduced export time by 50%.”

“Candidate brings a mix of business development and investment-style diligence experience across a crypto startup, healthcare software analysis, and US market-entry work. They have built outbound pipelines from scratch, supported diligence by benchmarking metrics and surfacing risks, and synthesized customer and market insights into actionable updates for senior teams.”