Vetted Authorization Professionals

“Built and owned major parts of a real-time distributed AI fraud-detection pipeline (ingestion, inference microservice integration, and automated action layer), optimizing latency and observability and reducing false positives by ~35%. Understands ROS/ROS2 concepts (nodes/topics/services) and planned hands-on ramp-up via ROS2 pub/sub exercises and Gazebo simulation, but has not worked on physical robots or ROS in production.”

“LLM/RAG engineer who has shipped production systems in high-stakes domains (fraud analytics at Mastercard and security compliance as a CI/CD gate). Strong focus on reliability: hybrid retrieval for latency, citation-backed outputs for trust, and code-driven eval/regression pipelines using golden datasets. Also built scalable OCR-based ingestion for messy classroom artifacts (handwriting, PDFs, whiteboard photos) using Go/Python and cloud services.”

“QA/automation engineer with experience at Riot Games’ player platform, owning E2E automation for mission-critical authentication/account flows using Playwright/JavaScript plus API automation. Built CI merge gates and nightly verification with Slack reporting, and repeatedly caught backend-driven session/authorization regressions before production. Known for stabilizing flaky UI tests via selector strategy and network intercepts, and for influencing design early with testability hooks and telemetry.”

Sri Harshitha Yannam

Screened

Junior Software Engineer specializing in AI/ML and cloud platforms

Austin, TX2y exp

“LLM/agent engineer who shipped a production "Memory Assistant" at HydroX AI, building a LangChain/LlamaIndex RAG memory pipeline on ChromaDB/FAISS with robust fallbacks (BERT/BART), prompt-injection mitigation, and 99.9% uptime monitoring. Also built a multi-step customer support agent using Rasa + OpenAI Assistants API with structured tool calling, guardrails, and human-in-the-loop escalation, and has experience hardening agents against messy ERP data via Pydantic validation, idempotency, and transactional outbox patterns.”

“Backend/data platform engineer who recently owned an end-to-end large-scale financial data platform delivering real-time decision support for finance and operations. Has hands-on experience modernizing legacy batch pipelines into AWS cloud-native ELT with parallel-run cutovers, strong data quality controls (dbt-style tests, reconciliation), and measurable improvements in runtime, cost, and SLA compliance. Also builds scalable, secure FastAPI microservices using Docker, ALB-based horizontal scaling, Redis caching, and managed auth with Cognito/Supabase plus Postgres RLS.”

“ML/Backend engineer with ServiceNow experience building production-grade inference services on FastAPI with Docker/Kubernetes (autoscaling, health checks) and strong reliability practices (monitoring, retries/timeouts, fallbacks). Delivered measurable improvements including 30% lower API latency and 18% higher model accuracy, and built A/B testing plus drift-triggered retraining loops to keep models stable in production.”

Pranav Chand

Screened

Senior AI/ML Engineer specializing in Generative AI and LLM platforms

ServiceNow, CA5y exp

“Backend engineer focused on multi-tenant enterprise AI personalization and recommendation platforms, combining ML/LLM intent extraction with deterministic policy guardrails for compliance and auditability. Has hands-on AWS experience (ECS/Lambda/DynamoDB/S3) and led a careful DynamoDB single-table migration using dual write/read, canary + feature-flag rollouts, and strong observability/security (JWT/OAuth2, RBAC, Postgres RLS).”

Utkarsh Mittal

Screened

Intern Data Scientist specializing in computer vision and LLM agents

Sunnyvale, CA0y exp

“Software engineering candidate with hands-on experience building and shipping LLM agents: created a production AI enrichment/coding agent at Covalent Metrology using Apollo.io + OpenAI, and built a Mistral hackathon router that dynamically selects among models to reduce token cost while maintaining quality. Also developed a real-time financial margin analysis agent that emails actionable insights and iterated on reliability issues (e.g., fixing misrouted emails, improving news relevance filtering).”

Srushti Milind Jamsandekar

Screened

Mid-Level Software Developer specializing in backend, cloud, and GenAI

CA, USA5y exp

“Full-stack engineer with fintech and AI feature experience who shipped an AI-powered project summary module in Next.js (App Router + TypeScript) with secure server-side fetching and route handlers to a FastAPI backend, then owned monitoring and performance fixes in production. Demonstrated measurable UX wins (30% faster dashboard loads) and strong backend fundamentals (Postgres indexing/EXPLAIN ANALYZE, SQS-orchestrated idempotent reconciliation workflows with DLQs and retries).”

“Backend/data engineer focused on AWS-based Python services and data pipelines: built a Django/DRF user management/auth platform deployed with serverless AWS (Lambda/API Gateway) and event-driven workflows (Step Functions/EventBridge), with CloudFormation + Jenkins for automated delivery and Secrets Manager/Parameter Store for secure config. Also delivered AWS Glue ETL from S3 to RDS with schema evolution controls and incident-driven improvements, and has demonstrated measurable SQL tuning impact (minutes-to-seconds).”

“Built and productionized an internal LLM-powered document Q&A system at Morgan Stanley using a LangChain-based RAG pipeline (FAISS + OpenAI) with AWS ingestion (S3/Lambda), handling 100k+ pages and cutting lookup time ~35% while keeping responses under 3 seconds. Strong on reliability: automated evals/CI (pytest + GitHub Actions), CloudWatch monitoring, drift detection (prompt drift and fraud-model drift), and security controls (IAM + app-level authorization) in a financial-services environment.”

Sarthak Vinayaka

Screened

Mid-Level Full-Stack Software Engineer specializing in enterprise AI, data pipelines, and scalable APIs

Redwood City, CA3y exp

“Forward-deployed engineer/tech lead who built an end-to-end demand planning and forecasting application for a major US steel manufacturer, integrating Snowflake data into the C3 platform with batch/MapReduce workflows, monitoring, and a React/TypeScript UI. Also productionized an enterprise LLM integration with structured outputs and authorization guardrails, reporting +30% stakeholder engagement and broad adoption across customer deployments.”

Yash Rangucha

Screened

Mid-level Software Engineer specializing in backend microservices and real-time streaming

Illinois, USA4y exp

“Built and owned an end-to-end LLM-powered enterprise retrieval pipeline at ServiceNow, spanning ingestion of structured/semi-structured sources through vector retrieval and real-time API serving. Focused heavily on reliability and quality (multi-stage validation, monitoring, evaluation pipelines) while also driving performance improvements (~35% faster responses) via caching, async processing, and SQL/query optimization.”

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.”

Chuks Onwuneme

Screened

Executive technology leader specializing in Healthcare IT, AI, and regulated SaaS

Seattle, WA24y exp

“Founder who raised friends-and-family capital in 2024, used it to build an initial product and develop patent-backed IP, then pivoted from AI impersonation detection to authorization and trust infrastructure for agentic workflows. Demonstrates strong strategic thinking around infrastructure products, customer-driven repositioning, and venture-backed startup dynamics.”

“Backend-focused engineer with strong .NET/Angular experience building enterprise financial and healthcare systems, including microservice APIs deployed with Docker/Kubernetes and AWS ECS. Demonstrates production reliability skills across secrets management (Secrets Manager/IAM), incident response (CloudWatch + Kafka failover), and data engineering patterns from SSIS ETL (data quality, incremental recovery), plus proven SQL tuning with a 10-minute report reduced to under 30 seconds.”

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.”