Vetted CI/CD Professionals

“AI Engineering Intern at The Etherloop building the backend for a healthcare lifestyle recommendation app, including a multi-agent RAG-based system that uses curated SME data plus web search to generate personalized supplement recommendations from user lifestyle details and blood biomarkers. Evaluates against 500+ SME ground-truth profiles with ranking metrics and focuses on HIPAA-aligned deployment, privacy/security, and guardrails to reduce hallucinations and unsafe outputs.”

“AI engineer with experience taking a GPT-4-powered GenAI career coach toward production on Azure AI Foundry, re-architecting the backend with hybrid (vector + keyword) search and RAG optimizations to cut latency by 50%. Also has client-facing TCS experience building healthcare ETL pipelines and delivering error-free monthly reports, plus current work analyzing agentic system reasoning traces and guardrail drift as an AI research fellow.”

“Data/ML engineer in financial services (Northern Trust) who built a production RAG-based LLM system to connect structured transaction/portfolio data with unstructured market and internal documents for risk teams. Strong in end-to-end pipelines (AWS Glue/Airflow/PySpark), entity resolution, and taking models from prototype to reliable daily production with performance tuning (LoRA + TensorRT) and monitoring.”

Ashutosh Khatavkar

Screened ReferencesStrong rec.

Mid-level SDET/Software Engineer specializing in test automation and CI/CD

Syracuse, NY3y exp

“AAA game QA professional from Ubisoft (For Honor) with deep live-service multiplayer experience. Known for owning network/competitive integrity risks and building a custom network simulation tool to reliably reproduce desync issues, accelerating debugging and saving 100+ hours. Strong end-to-end QA process skills spanning test planning, triage, regression, and release verification using JIRA/TestRail.”

“Full-stack engineer who built and scaled an AI-powered web product (React/Next.js + TypeScript/NestJS) with MongoDB, Redis, and RabbitMQ. Strong in rapid iteration while maintaining production quality—uses versioned APIs, feature flags, CI/CD, and observability (correlation IDs/structured logs) to ship frequently and debug distributed workflows. Also created an internal operations dashboard for real-time visibility and control of background jobs/AI workflows that was adopted quickly by ops and product teams.”

“Built and productionized an internal GenAI chatbot that makes company policy/SOP knowledge instantly searchable, using a secure RAG architecture on AWS (Bedrock/Titan embeddings/OpenSearch Serverless, Textract/Lambda/S3 ingestion, Claude 3 Sonnet). Demonstrates strong MLOps/orchestration experience (Airflow, Step Functions with Lambda/Glue/SageMaker) and a rigorous reliability approach (RAGAS metrics, A/B testing, citation validation, monitoring), including collaboration with compliance stakeholders via review dashboards.”

Amrit Srivastava

Screened ReferencesStrong rec.

Junior Software Engineer specializing in robotics simulation and machine learning

3y exp

“Undergraduate AI/robotics research assistant who built a city-scale robotics simulation stack for embodied question answering, including JSON-driven environment generation and a ROS 2 pipeline bridging Isaac Sim sensors (CV/LiDAR) to external ML/RL algorithms. Also created and deployed an open-source library workflow tool adopted across multiple local libraries, using GitHub Actions CI/CD for signed releases and automated updates.”

Bhavesh Ittadwar

Screened ReferencesStrong rec.

Senior Full-Stack Engineer specializing in scalable web and cloud systems

USA3y exp

“JavaScript engineer who built a Michelin-specific headless CMS forms platform based on apostrophe-forms, powering forms across 400+ Michelin websites. Designed an extensible, SOLID-aligned modular field architecture with a shared design system, cutting hundreds of lines of per-project code across 10+ implementations while driving cross-device compatibility and performance (BrowserStack, Lighthouse, SSR).”

Nicholas Pinero

Screened ReferencesStrong rec.

Mid-level Software Engineer specializing in Unity XR/VR training simulations

Remote, USA8y exp

“Unity/C# VR developer who owned a next-gen replay/review system end-to-end, improving determinism so recorded actions (e.g., shots) replayed consistently. Also built a Jenkins-triggered GameDriver-based VR QA automation suite that ran nightly builds and cut manual QA effort by ~75%, and contributed to Photon PUN multiuser mode with hands-on network debugging.”

“Robotics intern at the University of Delaware who built and debugged ROS2-based multi-robot coordination systems, focusing on real-time reliability (timestamp alignment, latency/jitter instrumentation, QoS/executor tuning). Also improved SLAM stability by fixing LiDAR/encoder synchronization and tuning state-estimation parameters, with a simulation-first workflow using Gazebo and Docker/CI for reproducible deployments.”

“AI Software Engineer (student employee) at University of Washington IT who helped deploy "Purple," a governed, explainable LLM platform on Azure used by 100,000+ students/faculty/staff. Independently led scalable reliability efforts by building automated agent quality/load/red-team testing and CI/CD health validation (Playwright/Node.js, Azure DevOps), and previously built an explainable AI scheduling assistant for clinical operations at Proliance Surgeons.”

“Backend/platform engineer who has owned a real-time data ingestion/processing/reporting API built with FastAPI, Redis, and Celery, including performance tuning via query/index optimization, caching, and async workers. Strong Kubernetes + CI/CD + GitOps (ArgoCD) experience, plus hands-on monitoring/logging (Prometheus/Grafana/ELK) and a Kafka/Spark real-time streaming project from their master’s program.”

“Built and shipped a production RAG system (“TROJAN KNOWLEDGE”) for answering questions over technical PDFs, using a 3-stage retrieval stack (BM25 + FAISS + cross-encoder) to lift F1 from 71% to 84%. Drove major performance gains with a 3-level cache (memory/Redis/disk) cutting latency from ~200ms to ~10ms, and added Prometheus/Grafana monitoring plus LangChain-based fallback logic to handle OpenAI rate limits under load.”

“Infrastructure/platform engineer with end-to-end ownership across Kubernetes and VMware/vSphere, emphasizing automation (Terraform/Ansible), phased upgrades, and reliability validation via testing/failover/monitoring. Has operated hybrid on-prem VMware to AWS environments with VPN/Direct Connect, BGP routing, and security controls, including resolving production connectivity instability and adding redundancy.”

Sudheer koki

Screened ReferencesStrong rec.

Mid-level AI/ML Engineer specializing in predictive modeling, data pipelines, and RAG systems

Florida, USA5y exp

“Built and productionized an LLM-powered internal knowledge search system in a regulated environment, using embeddings/vector DB retrieval with strict grounding and confidence gating to reduce hallucinations. Reported ~45% accuracy improvement over keyword search and implemented end-to-end orchestration, monitoring, CI/CD, and incremental re-indexing to manage latency and data freshness while driving adoption with business stakeholders.”

“Infrastructure/automation engineer with experience bridging post-acquisition environments (Pandora + SiriusXM) by building an API-driven integration to provision Debian workloads on RHV while preserving iPXE-based imaging workflows. Strong in deep debugging across virtualization/network/OS layers (e.g., resolving virtio/vCPU contention causing network/NFS issues) and in extending automation tooling via custom Ansible/Python modules. Also has exposure to biomanufacturing on-prem devices (Hamiltons, shakers) alongside AWS microservices.”

“Software engineer with JPMorgan Chase experience building a real-time operations console backend on Spring Boot/Kafka/Kubernetes and resolving peak-load latency through profiling, indexing, caching, and async processing. Also built and owned an AI-driven digital-archives metadata pipeline during a master’s at UNT using OCR + LLaMA-based prompting with validation, near-human accuracy, and human-in-the-loop guardrails.”

Sesha SaiSrikar Gaddam

Screened ReferencesStrong rec.

Intern Mechanical Engineer specializing in robotics design and CAD

Remote1y exp

“Robotics engineer focused on MATLAB-based simulation and system-level/mechanical aspects of robot safety and coordination. Built an obstacle detection/collision-avoidance approach for a SCARA robot in shared human workspaces and optimized a swarm robotics simulation via priority-based task allocation and congestion-aware routing; currently ramping up on ROS concepts and interested in Gazebo + Docker/CI/CD for end-to-end robotics workflows.”

Noah Bertschmann

Screened ReferencesStrong rec.

Mid-level Robotics Software Developer specializing in ROS and autonomous mobile robots

Kitchener, Canada4y exp

“System-level robotics software engineer with production experience in both ROS 1 and ROS 2 who served as technical owner for an initial ROS1→ROS2 migration, including catkin→ament/colcon and refactoring core communication nodes. Strong in hardware-validated integration work—debugged intermittent message drops by tuning ROS 2 QoS for embedded firmware interfaces and stabilized real-time navigation behavior through timing/telemetry analysis and cross-team coordination.”

Brandon Pav

Screened ReferencesStrong rec.

Executive CTO specializing in cloud architecture, DevSecOps, and scalable SaaS platforms

Indianapolis, IN13y exp

“Founder of Pavtek Consulting LLC who acts as a hands-on technology leader for startups, building MVPs and full-stack AI products, custom ERPs, integrations, and AI agent chat tools. Notably led a major turnaround at Dyknow (EdTech), cutting major cloud waste and moving the business from a $500k annual loss to double profitability within two years before a successful acquisition.”

Timothy Flechtner

Screened ReferencesStrong rec.

Executive Technology & Product Leader specializing in games, platforms, and real-time systems

23y exp

“Engineering leader with gaming and fintech/trading-firm experience who built a sponsor-funded gaming rewards platform (AmEx-style) requiring integrations across Steam/Epic/Xbox/PlayStation and Discord. Emphasizes production-grade, 12-factor delivery with Terraform/Docker/CI/CD and automated testing, plus pragmatic org scaling and remote-team culture built on aligned autonomy and trust.”