Vetted SQL Professionals

“Front-end engineer with significant ownership of sophisticated enterprise admin experiences in Cisco Webex Control Hub. Stands out for building permission-aware, route-driven UI architecture and solving tricky browser/CSS integration issues across shell and remote-entry boundaries while keeping the experience polished and consistent for expert users.”

“MSR robotics candidate who led a 4-person project building a ROS2 MoveIt wrapper for a Franka Emika arm and integrating a RealSense-based vision pipeline for color-based object tracking/sorting. Also building a quadruped with ROS on Raspberry Pi, bridging ROS commands through a motor driver to TTL-controlled motors, and expanding from Python ROS development into C++ for navigation/LiDAR/SLAM work on TurtleBot3.”

“Robotics software engineer who has built end-to-end pipelines spanning backend/data processing through model interfaces and hardware integration. Has hands-on ROS2 experience building Python nodes and debugging real-time behavior via profiling, publish-rate tuning, and latency fixes, plus experience standardizing multi-robot communication with QoS adjustments. Uses Gazebo simulation and Docker/CI/CD to catch integration issues early and speed iteration.”

“Built and shipped open-source LLM/RAG systems, including a generative AI assistant grounded on ~30,000 scraped university web pages, improving response accuracy ~30% by moving from TF-IDF-only retrieval to a hybrid sentence-transformer approach with fallback controls. Also partnered with non-technical leadership at Securi.ai to deliver real-time predictive analytics dashboards (Elasticsearch + Jira/ServiceNow) that reduced project overhead by 18%.”

“Software engineer focused on reliability and scalable systems: built React/TypeScript dashboards backed by Java/Spring Boot APIs and designed Kafka-based microservices with strong contract/versioning discipline. Known for shipping incremental improvements with tight feedback loops and for creating internal observability tools that streamline on-call and incident diagnosis under high-traffic conditions.”

“Backend-focused Python engineer who built an end-to-end personalized chatbot service integrating Amazon Redshift context retrieval with Amazon Bedrock, including prompt construction and production-grade reliability controls. Strong platform experience deploying containerized services to Kubernetes with GitOps/ArgoCD, plus hands-on Kafka streaming and phased infrastructure migration execution.”

“Robotics-focused Python developer who built autonomous navigation for a differential-drive robot using onboard vision and AprilTag detection, including pose estimation and coordinate frame transformations for localization and motion planning. Also has practical backend performance experience using Redis TTL caching to speed responses and reduce server load, plus basic PostgreSQL query/index optimization.”

“Search/backend engineer with hands-on experience improving Apache Solr-based search systems end-to-end (indexing strategy changes, ETL updates, and Java/Spring Boot Search API work). Demonstrated production rigor with QA partnership, A/B testing, and rollback-safe kill switches, plus measurable product impact (e.g., +1.5% add-to-cart) and operational troubleshooting including traffic/security mitigation.”

“AI/ML practitioner who built an Indian Sign Language recognition system (MediaPipe hand keypoints + CNN/RNN) as an accessibility-focused teaching aid, iterating closely with advocacy groups and educators and reaching 92% accuracy. Also has production-scale data migration experience at Saasgenie, using Kubernetes pod parallelization to migrate 1M+ ITSM records with a 5x throughput gain under API rate limits.”

“Full stack engineer in the financial/thematic investing domain who built end-to-end applications on AWS. Notably redesigned a slow portfolio analytics workflow by offloading heavy computations to scheduled AWS Lambda jobs and caching results in DynamoDB (TTL), cutting API latency from ~5 seconds to under 300ms while supporting data-heavy daily market processing.”

“LLM/agentic systems builder at Verizon who deployed a LangGraph-orchestrated multi-agent ticket-automation platform with RAG (FAISS) to replace brittle rule-based bots. Improved routing correctness by ~30–40%, hit ~300ms latency targets via model routing, and reduced ops workload by ~60% through tight iteration with non-technical stakeholders and strong testing/observability practices.”

“Backend-heavy full-stack engineer with experience at Intuit (TurboTax Live) and Paytm payments, building and scaling Java/Spring Boot microservices for high-traffic transaction systems. Has hands-on wins improving peak-load performance using Redis/disk caching and Kafka event-driven patterns, plus React/Redux work for web app integration and strong monitoring practices with ELK.”

“Customer support professional with Scrum Master and Product Owner certifications who has handled high-stakes account security incidents (including locking down an account to protect over $200k) and troubleshot live data feed integrations (XML/socket) by identifying IP whitelisting mismatches. Emphasizes transparent stakeholder communication, escalation, and building internal wiki documentation to prevent repeat issues.”

“Solutions Engineer focused on application and platform security for enterprise cloud-native deployments, advising customers on threat modeling and secure CI/CD practices across AWS and Kubernetes. Has implemented SCA/container scanning and vuln checks in pipelines, tuned thresholds to reduce false positives, and driven outcomes like faster security approvals and smoother production rollouts. Troubleshot high-load Kubernetes failures (OOMKills, registry throttling) and turned fixes into a standard tuning guide.”

“Backend/platform engineer with payroll domain depth who built high-volume payroll processing microservices (Java/Spring Boot, Kafka, PostgreSQL, Redis) on AWS Kubernetes and debugged major peak-cycle latency by redesigning transaction boundaries and moving to async Kafka processing (>50% latency reduction). Also shipped an LLM-powered HR assistant using RAG with strong security/guardrails (RBAC, PII masking, audit logs) that cut support tickets by 40%, and designed reliable multi-step agent workflows with retries, circuit breakers, and idempotency.”

“Backend/AI workflow engineer with PayPal experience building workflow-driven financial compliance systems (Python/Java, Postgres, AWS/EKS) at thousands of executions/day. Has shipped production LLM-powered document extraction with strict schema/rule validation, auditability, and human-in-the-loop fallbacks, and has deep expertise in reliability (idempotency, locking, state machines) and Postgres performance tuning.”

“Backend/LLM engineer who built a production-critical Amazon Bedrock + RAG correction and compliance layer for employee communications, integrating tightly with existing Spring Boot/AWS microservices to reduce manual review while keeping outputs explainable and auditable. Also designed an event-driven system processing 10M+ events/day (SQS/Lambda/DynamoDB/Elasticsearch) and handled on-call incidents with strong observability and reliability patterns (idempotency, retries, hotspot mitigation).”

“Backend/ML systems engineer with Stripe payments experience who built an asynchronous processing upgrade handling millions of API requests, cutting peak latency ~20–25% while preserving strict financial consistency via idempotency-safe retries and robust validation/fallbacks. Also built scalable ETL pipelines for messy CSV/Excel/API data with strong observability (structured logging/monitoring) and reliability mechanisms.”

“Data engineer with healthcare (CVS Health) experience who migrated production PySpark workloads to native BigQuery SQL and built a Great Expectations-based validation microservice on GKE (Flask + REST) integrated into Cloud Composer. Has operated high-volume pipelines (~300–400GB/day) and designed external vendor ingestion on AWS (Lambda/Step Functions/Glue) with schema-drift detection, alerting, and backfill-safe controls to protect downstream Snowflake/BigQuery tables.”

“Built and shipped a production enterprise RAG knowledge assistant that returns grounded, cited answers and uses confidence-based fallbacks (clarifying questions/abstention) with monitoring and compliance controls for sensitive data. Implemented end-to-end agent orchestration (function calling, structured JSON, state, retries/rate limits) plus eval/feedback loops, and achieved a reported 30–40% improvement in knowledge-task completion time while reducing hallucinations via retrieval improvements.”

Lavanya Chilakalapudi

Screened

Mid-level Full-Stack Developer specializing in cloud-native web apps and APIs

Tampa, FL5y exp

“Backend engineer with experience building microservice-based systems that integrate LLM workflows (code review suggestions, documentation generation, test scaffolding) using REST APIs, Celery/Redis, and OpenTelemetry for observability. Demonstrates hands-on database and performance optimization in PostgreSQL/SQLAlchemy (bulk inserts, lock mitigation, cursor-based pagination) plus multi-tenant data isolation via tenant-aware models, middleware scoping, and schema/row-level strategies.”

ABHIJOY SARKAR

Screened

Senior AI Engineer specializing in LLMs, agentic systems, and MLOps

San Francisco Bay Area, CA8y exp

“Built and shipped PromptGuard, a production middleware proxy that secures GenAI RAG/agent systems against prompt injection and unsafe tool use using risk scoring, graded policy actions, and least-privilege tool gating. Also replaced LangChain abstractions with a custom state-machine runner for a production voice agent to reduce latency and improve traceability, and delivered a clinic call assistant by converting front-desk/doctor requirements into scenario-based guardrails and measurable evals.”

Madhu Swetha Kommi

Screened

Intern Full-Stack Software Engineer specializing in cloud data pipelines and internal tools

1y exp

“Built an internal Meta tool (HiVA Bot) for notification customization and end-to-end task tracking around advertiser-reported issues, including chat-thread creation, org-hierarchy opt-ins, SLA reminders, and search/typeahead features. Implemented the system with a Java/Spring Boot microservices approach and asynchronous patterns, and supported adoption via internal wiki documentation.”