Vetted Python Professionals

“Backend/platform engineer who has owned end-to-end production systems in financial/claims domains, including a transaction analytics microservice platform processing ~10M daily operations and cutting latency from ~150ms to <70ms. Also productionized an LLM-powered monitoring/alerting capability (Llama 3 + FastAPI) with prompt design, guardrails, and production evaluation, and led monolith-to-microservices modernization on AWS using feature flags and parallel runs.”

“Software engineer with hands-on ownership of both fintech checkout improvements (saved payment methods/one-click checkout with tokenization and feature-flag rollouts) and production LLM/RAG systems for customer support. Demonstrates strong operational rigor via guardrails, evaluation loops integrated into CI/CD, and scalable data pipelines handling messy PDFs/CSVs/logs with reliability and observability.”

“Built a production internal LLM-powered knowledge assistant using a RAG architecture (Python, LLM APIs, cloud services) that answers employee questions with sourced, grounded responses from internal documents. Demonstrates strong practical depth in retrieval tuning (chunking/metadata filters), orchestration with LangChain, and production reliability practices (latency optimization, automated embedding refresh, evaluation metrics, logging/monitoring) while partnering closely with non-technical operations teams.”

“Distributed-systems engineer applying robotics-style patterns to software: built "Vibecheck," a high-throughput real-time video + OS-telemetry fusion and analysis system (500+ MB/session) with strict latency constraints. Strong in containerization and CI/CD (Docker, GitHub Actions) and in designing fault-tolerant, event-driven architectures (Kafka/RabbitMQ), plus hands-on debugging of multi-agent coordination using blackboard + watchdog/circuit-breaker control patterns.”

“Built and shipped a production browser automation LLM agent with a structured 4-stage workflow (plan/browse/extract/verify), emphasizing reliability via schema validation (Pydantic), constrained tool use, and contextual retry loops. Reports ~60% accuracy on the WebArena benchmark and monitors runs via console output and the Agno framework GUI, prioritizing accuracy over speed.”

“Data engineer with healthcare and enterprise experience (Molina Healthcare, Dell Technologies) building and operating high-volume batch + streaming pipelines across AWS and Azure. Strong focus on data quality (schema validation, fail-fast checks), reliability (monitoring/alerts, retries), and performance tuning (Spark/partitioning), with measurable runtime reduction and improved downstream trust.”

Kyle Holmquist

Screened

Senior Gameplay Engineer specializing in Unity/Unreal gameplay, AI, and narrative systems

11y exp

“Game developer with 13 years in the games industry who built a Unity VR feature using machine learning to recognize player-drawn spell symbols, training an accurate neural network from an existing dataset and solving tricky screen-space/world-space input constraints. Actively uses AI assistants for targeted code snippets and code review while emphasizing understanding over "vibe coding," and is interested in expanding into multiplayer/networking.”

Kutay Demiralay

Screened

Junior Controls & Autonomy Engineer specializing in robotics and trajectory optimization

Seattle, WA3y exp

“MS thesis work in the University of Washington Autonomous Controls Lab building a full quadrotor guidance/navigation/control stack, including high-fidelity dynamics modeling and an SCP trajectory optimizer made robust to wind via trust regions and MPC-style replanning. Also built an autonomous RC car using ROS on Jetson Xavier with ZED stereo/VIO, implementing perception (point cloud filtering/clustering) and state estimation while addressing real-time synchronization and latency challenges.”

Shaun Ames

Screened

Senior Unreal Engine Game Developer specializing in multiplayer systems and VR

California, United States9y exp

“Gameplay/network systems developer with shipped experience at Narsun Studios and Volition, including end-to-end ownership of a custom multiplayer session system for a VR title built on Unreal Online Subsystem with dedicated servers on AWS GameLift and PlayFab backend. Strong in profiling-driven optimization, scalability/load testing, and data-driven progression/balance (GAS), with telemetry-led changes that improved retention by ~20%.”

Harshini Jaligama

Screened

Senior Full-Stack Java Developer specializing in cloud-native microservices and FinTech

Remote, USA5y exp

“Full-stack engineer (5+ years with Java/Spring Boot and React) who has built and deployed AWS-based microservices platforms using Kafka for real-time rewards/promotions and large-scale telemetry analytics. Demonstrates hands-on scalability expertise (partitioning, consumer groups, durability/acks, idempotency) and production-minded delivery practices (CI/CD, Docker, testing, Swagger, monitoring).”

“Unity/C# mobile game engineer based in Belgrade who has owned and shipped complex meta-systems (shop/battle pass/tournaments) and real-time PvP using Photon, with a strong focus on performance (profiling, memory/GC, draw calls) and live stability. Notably handled a China launch by abstracting regional SDKs behind DI-based interfaces and using Addressables for localized assets, keeping the global codebase clean while maintaining high performance.”

“Data engineer (Charles Schwab) who took ownership of an unstable, ambiguous nightly financial data pipeline and rebuilt it into a reliable, incremental AWS Glue/Airflow/Redshift system feeding Power BI. Created a custom Python data-quality framework with hard-stop gating and schema drift detection, improving integrity (99.9%), cutting runtime (~20%), and reducing incidents/tickets (35% fewer schema-related dashboard incidents; 30% fewer investigations).”

Yaswanth Thota Thota

Screened

Mid-level Data Analyst specializing in financial risk and healthcare analytics

AZ, USA4y exp

“AI/ML engineer focused on real-time, production-grade LLM systems, with a robotics-adjacent mindset around latency/accuracy tradeoffs and modular pipelines. Built a scalable RAG-based assistant orchestrated as microservices on Kubernetes with Kafka async messaging, ONNX/quantization optimizations, and monitoring (Prometheus/Grafana), citing a ~35% hallucination reduction; has also experimented with ROS Noetic/Gazebo to understand ROS concepts.”

Jaideep bommidi

Screened

Senior ML Engineer & Data Scientist specializing in LLM agents, retrieval/ranking, and MLOps

Denton, TX8y exp

“Machine Learning Engineer currently at Webster Bank building an enterprise-scale LLM agent for Temenos Journey Manager/Maestro, using RAG-style multi-stage retrieval with FAISS/Pinecone, hybrid dense+sparse search, and LoRA fine-tuning optimized via NDCG/MAP and A/B testing. Previously handled messy incident/telemetry data at Deuta Werke GmbH with deterministic + fuzzy entity resolution, and has strong production data engineering experience across Spark/Hadoop and Python ETL systems.”

Sai Harshith Tanguturi

Screened

Mid-Level Software Engineer specializing in Java microservices and AWS cloud-native systems

Grapevine, TX3y exp

“Full-stack engineer who has owned customer-critical analytics and course intelligence platforms end-to-end (React/TypeScript + Node/Express + SQL), including an internal self-serve Reporting & Analytics Center adopted by 1,000+ users. Demonstrates strong systems thinking across performance (2× faster heavy reports), reliability (feature flags, testing), and distributed architecture (RabbitMQ microservices with idempotency, DLQs, and correlation-ID observability).”

Prachika Agarwal

Screened

Senior Solutions Architect and Data Analyst specializing in cloud data platforms and experimentation

New York, NY4y exp

“Software engineer who built and scaled an internal automation/auditing tool for analyzing Google and Adobe tagging containers, adopted by 13 internal clients and saving ~15 hours per audit. Has experience shipping containerized, Kubernetes-orchestrated systems and integrating OpenAI APIs into an agentic chatbot feature (plus prior NLP chatbot work during a Cyber Peace Foundation internship).”

Bryan West

Screened

Senior Software Engineer specializing in AI, cloud infrastructure, and full-stack development

Chantilly, VA17y exp

“ML/NLP engineer who built a production system that converts large-scale unstructured text into a connected, searchable knowledge base using spaCy + Sentence Transformers/FAISS and a Neo4j knowledge graph, with BERTopic and XGBoost for organization/labeling. Strong focus on production-grade Python workflows (FastAPI/Celery, Pydantic validation, Docker, AWS ECS/Lambda) and robust entity resolution with measurable precision/recall and human review for low-confidence matches.”

Sai Vamsi

Screened

Mid-Level Software Engineer specializing in backend microservices and cloud-native systems

TX, USA4y exp

“ServiceNow engineer who built an AI-powered ticket summarizer end-to-end (RAG with vector DB + GPT, Redis latency optimizations, fallback summarization, and a React UI widget for agent feedback). Also has hands-on ROS 2 experience building real-time sensor-fusion nodes (LiDAR/IMU), debugging SLAM/navigation issues via rosbag + EKF tuning, and bridging heterogeneous robots by translating ROS 2 topics to MQTT/JSON. Strong DevOps background with Docker, Jenkins CI/CD, and Kubernetes orchestration for scalable deployments.”

Sahachel Flores

Screened

Mid-Level Backend Software Engineer specializing in enterprise systems and applied AI/ML

Mountain View, CA6y exp

“Support engineer with IBM DFSMS OAM experience who restored a production TS7770 environment during a TS7760→TS7700 migration by using logs, SLIP traps, and dump analysis to pinpoint an SMS configuration (SCDS) issue, then partnering with the customer to redo the migration successfully. Also built a personal agentic news selector system and emphasizes documentation improvements and customer education to prevent recurring incidents.”

ESHWANTH D. G

Screened

Mid-level Robotics Software Engineer specializing in autonomous perception and sensor fusion

CA, USA4y exp

“Robotics engineer with Honeywell and Tata Motors experience deploying ROS/ROS2 autonomous mobile robot fleets into live factory environments, integrating sensors, safety PLCs, and on-prem services. Known for solving end-to-end latency and stability issues (including network spikes under load) using gRPC, Docker, and improved diagnostics—cutting diagnosis time from hours to minutes and achieving sub-150 ms control response.”

Jeetendra Girish Vasisht

Screened

Junior Software Engineer specializing in cloud-native microservices

Bangalore, India2y exp

“Backend engineer (Nokia) who designs and migrates cloud-native microservices at scale, including a secure low-latency system handling 500k+ daily transactions. Strong in Kubernetes/OpenShift operations, CI/CD standardization, and production security (OAuth2/JWT/RBAC) with SOC2-aligned controls and zero critical security incidents. Demonstrated expertise in safe migrations (canary/blue-green, dual writes, reconciliation) and concurrency correctness in real-time systems.”

Szymon Kościelniak

Screened

Senior Unity Developer specializing in mobile and VR/PC games

Warsaw, Poland7y exp

“Unity gameplay engineer from Moonactive who rewrote the gameplay engine for ZenMatch, maintaining two engines in parallel via a separation layer to improve robustness/scalability and make new content easier to ship. Also implemented multiplayer for a client prototype using the Onion networking framework and is familiar with Photon Fusion concepts.”

Esha Gangam

Screened

Mid-level AI/ML Engineer specializing in LLMs, RAG, and MLOps

USA4y exp

“GenAI/ML engineer from Deloitte who built and shipped a production RAG-based internal search assistant for support teams, delivering quantified operational gains (20% effort reduction, 35% faster manual lookup). Experienced in enterprise-grade LLM reliability (grounding/hallucination control), compliance/security constraints, and rapid release cycles using CI/CD, MLflow, and orchestration tools (Airflow, Databricks Jobs, LangChain).”

Sai Chatrathi

Screened

Mid-level AI/ML Engineer specializing in healthcare analytics and MLOps

NY, USA4y exp

“Built and deployed a production LLM-powered lesson adaptation platform for K–12 educators that personalizes content for multilingual and neurodiverse students using RAG and content transformation. Owned the full stack from FastAPI backend and OpenAI integration through reliability/safety controls, latency/cost optimization, and weekly shippable modular APIs, iterating directly with curriculum stakeholders to reduce hallucinations and improve educator trust.”