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Vetted Bash Professionals

Pre-screened and vetted.

BashPythonDockerCI/CDGitAWS
CS

Chaitanya Sachdeva

Screened

Mid-level Applied AI Engineer specializing in LLM infrastructure and model optimization

San Jose, CA3y exp
AMDUSC

“LLM engineer who has deployed privacy-preserving, real-time workplace risk monitoring over massive enterprise chat/email streams, tackling latency, hallucinations, and extreme class imbalance with model benchmarking, RAG + fine-tuning, and a pre-filter alerting layer. Also built an agentic legal contract drafting system (Jurisagent) using LangGraph/LangChain with deterministic multi-agent control flow, structured outputs, and reliability-focused evaluation/telemetry.”

PythonC++BashLangChainLangGraphNumPy+104
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YP

Yeshwanth Pulapa

Screened

Mid-level AI/ML Engineer specializing in Databricks, MLOps, and real-time fraud detection

The Colony, TX4y exp
DatabricksUniversity of North Texas

“ML/LLM engineer building production, real-time fraud detection for financial transactions using a two-tier architecture (fast ML + GPT) to deliver both low-latency decisions and analyst-friendly risk explanations. Experienced orchestrating end-to-end retraining, drift monitoring, and automated model promotion with Databricks Jobs/Workflows and MLflow, and partnering closely with fraud analysts to tune alerts, thresholds, and dashboards.”

A/B TestingApache AirflowApache KafkaApache SparkAWSAWS Lambda+93
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NM

Nathan Moore

Screened

Principal Architect specializing in SRE, DevOps, and large-scale cloud/CDN platforms

Dallas, Texas14y exp
Inertia LabsUCLA

“Engineering leader who drove the conception, PRD, architecture, and delivery of MaxCDN’s next-generation CDN platform ("E2"), including control plane work, hardware deployment planning, and observability/billing data processing. Also built Krypton Labs’ engineering team from the first hires, using a flat Agile structure and emphasizing constructive conflict, strong documentation, and remote-team accountability.”

AgileAmazon EKSBashData EngineeringData ModelingDevOps+84
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SK

Shanmukha Koganti

Screened

Mid-level AI/ML Engineer specializing in recommender systems and edge computer vision

Bay Area, CA6y exp
ShopifyUniversity of North Texas

“ML/AI engineer with production experience at Shopify and Intel, building a deep learning product ranking system that lifted add-to-cart ~14% and serving real-time similarity search via FAISS+Redis under <20ms latency at massive scale. Also deployed computer vision models to 100+ retail edge locations using Docker/Ansible/k3s with zero-downtime rollouts, and applies strong MLOps practices (A/B testing, canary/shadow, observability) plus performance optimization (OpenVINO, INT8).”

A/B TestingAgileAnsibleApache KafkaApache SparkAWS+170
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AV

Alex Vo

Screened

Staff Backend Software Engineer specializing in telemetry pipelines and observability

San Jose, CA3y exp
VMwareUC Irvine

“Backend engineer from VMware focused on proprietary enterprise systems (monitoring tools, data pipelines, and APIs). Drove a ClickHouse migration POC (local to remote host) using a dual-write/cutover approach and source-level debugging across Node/driver differences during a Node 12→20 upgrade, and delivered measurable performance gains (~20% CPU/memory improvement) through batching and streaming ingestion.”

Backend DevelopmentNode.jsTypeScriptSQLREST APIsAPI Design+60
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HY

Houssain Youssfi

Screened

Mid-level AI/ML Engineer specializing in telematics, embedded systems, and MLOps

Mossville, IL5y exp
CaterpillarGeorgia Tech

“Built and deployed a retail customer review intelligence platform by fine-tuning BERT for sentiment/topic extraction and pairing it with a recommendation component. Demonstrates strong production ML rigor (error analysis, relabeling/active sampling, thresholding/guardrails, OOD checks) and AWS-based orchestration at scale (Lambda + SageMaker with batching and concurrency controls), plus proven ability to align non-technical stakeholders on measurable outcomes.”

AWSAWS LambdaAnomaly DetectionBERTBashBusiness Intelligence+136
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BP

Bhargava Prabu Reddy Mallikarjuna

Screened

Mid-Level Full-Stack Software Engineer specializing in automation, microservices, and cloud deployments

Cupertino, CA3y exp
AppleUniversity of Central Missouri

“Full-stack engineer with experience at Apple, Walmart, and a healthcare startup (Legacy), building customer-facing PWAs and internal platforms. Delivered HIPAA-compliant clinician/patient workflows with rapid weekly releases and measurable engagement gains, and built scalable automation/testing and real-time analytics systems using Next.js/React/TypeScript, Node/FastAPI, Redis, and PostgreSQL.”

AgileAngularAngularJSAuthenticationAutomationBash+77
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HR

Harshana Ragipindi

Screened

Mid-level Support/Software Engineer specializing in incident response, automation, and AWS monitoring

USA4y exp
AmazonUniversity of North Texas

“Built and owned end-to-end travel booking and baggage fee calculation platforms used by both customer support and customers, emphasizing fast iteration with automated guardrails and production visibility. Experienced designing TypeScript/React systems and operating RabbitMQ-based microservices at scale, including disciplined event contracts, idempotent consumers, and schema evolution strategies. Also created an internal real-time troubleshooting/pricing console that replaced fragmented tools and improved support resolution workflows through pilot-led adoption.”

PythonBashPowerShellSQLSaaSLinux+82
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RK

Rutuja Kawade

Screened

Mid-level Software Engineer specializing in cloud infrastructure and distributed systems

Atlanta, GA3y exp
RakutenGeorgia Tech

“Cloud infrastructure/product engineer with end-to-end ownership of cloud-native storage/observability products, including taking an internal CMS to Google Cloud Marketplace and scaling to ~40,000 deployments. Strong in Kubernetes-based platforms (Operators, microservices, RabbitMQ) and performance/scalability work (e.g., 200% cluster capacity increase) plus internal tooling that materially improved SRE/QA debugging and release velocity.”

PythonCC++GoJavaBash+115
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AZ

Alex ZhuZhou

Screened

Intern Full-Stack Software Engineer specializing in AI/LLM platforms and data systems

Berkeley, CA2y exp
EmbraerUC Davis

“Backend/LLM engineer with experience productionizing RAG systems (legal-case natural language querying) and optimizing for latency/cost, including a reported ~40% reduction via Redis caching and batching. Built monitoring and real-time debugging workflows (FastAPI, structured logging, correlation IDs, sandbox repro) and regularly delivered technical demos/workshops. Also partners with BD/sales to translate LLM capabilities into business value, including ESG-metric extraction from corporate filings.”

PythonTypeScriptJavaScriptJavaNode.jsSQL+78
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FL

Felix Li

Screened

Intern Software Engineer specializing in data pipelines and full-stack web development

New York, NY1y exp
RadarUniversity of Waterloo

“Internship at Radar (geolocation infrastructure) where they owned automation of multiple geospatial data ingestion pipelines (including US/Canadian address ingestion), orchestrating Spark (Scala) jobs via Python-based Airflow and using GitOps-style CI/CD workflows.”

AWSBashCC++CypressData Pipelines+60
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JA

Jeevan aher

Screened

Junior AI Engineer specializing in fraud detection, credit risk, and LLMs in FinTech

Remote, USA3y exp
JPMorgan ChaseUniversity of Illinois Urbana-Champaign

“AI engineer with production experience building a high-accuracy (98%) fraud detection system operating at real-time latency (1–2s) over millions of transactions, using a multi-model pipeline approach to meet performance constraints. Also implemented Airflow-orchestrated workflows (DAGs, retries, alerts) to replace brittle cron scripts and is currently pursuing a master’s project on real-time ASL-to-text conversion.”

PythonRSQLJavaScriptBashC+107
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JS

Jason Salas

Screened

Senior QA Engineer specializing in game quality ownership, automation, and analytics

Los Angeles, California9y exp
Riot GamesArizona State University

“QA/engineering background spanning Riot Games (VALORANT leaderboard systems) and early-stage startups. Has hands-on experience improving performance and reliability via caching, rate limiting, deduplication/idempotency, and shipping/validating high-stakes production hotfixes; also builds Next.js/TypeScript projects and automation/internal tools (Python).”

AngularPythonJavaScriptSQLUnreal EngineDatabricks+101
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PP

Pranav Pansheriya

Screened

Mid-level Cloud Support Engineer specializing in AWS microservices and payments APIs

Anaheim, CA4y exp
StripeCalifornia State University, Fullerton

“Customer-facing technical support/solutions professional with experience at Stripe and Intuit helping developers take payment API and webhook integrations from testing to production. Uses Datadog and AWS CloudWatch to diagnose real-time production issues (e.g., webhook signature validation errors causing retries/delays) and unblocks customer deployments through hands-on, developer-oriented guidance.”

AWSAmazon EC2AWS IAMAmazon CloudWatchAmazon VPCKubernetes+70
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VY

Vagmin Yadav

Screened

Junior Software Engineer specializing in backend systems, ML pipelines, and DevOps

Pune, India2y exp
Unbox RoboticsGeorgia Tech

“TypeScript backend engineer in the robotics domain with hands-on experience building low-latency (20–40ms) production systems using RabbitMQ, Redis, and HA PostgreSQL (Patroni). Has owned end-to-end services supporting 15 clients via config-driven architecture, with strong CI/CD, automated testing, and observability (OpenTelemetry) practices, plus API versioning/deprecation using Keycloak auth.”

PythonC++GoJavaScriptSQLFastAPI+92
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SR

Sanjana Reddy

Screened

Mid-Level Software Engineer specializing in cloud-native microservices and AI/ML integration

Remote, USA4y exp
BrexArizona State University

“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%.”

AngularAnsibleApache KafkaArgo CDAWSAWS CodePipeline+253
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PT

Parth Tusham

Screened

Intern Software Engineer specializing in systems, cloud, and security

Sunnyvale, CA1y exp
NokiaTexas A&M University

“Systems and infrastructure engineer pivoting toward robotics software; brings strong low-level debugging, multithreaded systems, and networking experience where correctness and timing matter. Has hands-on experience using Docker and CI/CD to build reproducible test/evaluation environments (thesis), and proposes a disciplined, contract-driven approach to distributed communication and real-time performance debugging.”

CC++JavaPythonGoRuby+85
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KP

Kush Parmar

Screened

Entry-Level Computer Engineer specializing in embedded Linux, verification, and aerospace systems

Blacksburg, VA2y exp
Virginia TechVirginia Tech

“Software Design Lead on a NAVAIR-sponsored senior design capstone building an Unreal Engine 5 UAV/LiDAR simulation to support sensor spoofing detection. Reverse-engineered and standardized LiDAR packet formats and integrated the sim with Simulink and an NVIDIA Jetson Orin Nano over Ethernet to enable stable real-time SIL/HIL testing, leveraging strong Linux/kernel networking knowledge to debug latency and packet loss.”

Neural NetworksLinuxPythonAPI DevelopmentCC+++106
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AS

ABHIJOY SARKAR

Screened

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

San Francisco Bay Area, CA8y exp
FlipkartIIT Ropar

“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.”

AWSBashCI/CDData PipelinesDockerGit+76
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AJ

AshokKumar Jakkula

Screened

Mid-level Robotics Engineer specializing in autonomous systems, perception, and simulation-to-real

California, USA3y exp
MetaUC Riverside

“Robotics software engineer focused on real-time mapping and SLAM in unstructured environments, combining camera-based navigation, GTSAM/iSAM2 pose-graph optimization, and nvBlox ESDF mapping with strong real-time performance on both RTX 4070 and Jetson Orin. Has hands-on ROS 2 + Docker integration experience and has built Isaac Sim plugins/ROS 2 packages to make LIO-SAM work in simulation, plus work on decentralized multi-robot SLAM with heterogeneous LiDARs and edge map building.”

BashComputer VisionGazeboMATLABOpenCVPython+125
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LC

Lavanya Chilakalapudi

Screened

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

Tampa, FL5y exp
DatabricksUniversity of South Florida

“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.”

AjaxAnsibleApache AirflowApache KafkaApache SparkAPI Gateway+164
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SV

Skanda Vyas Srinivasan

Screened

Intern Software Engineer specializing in full-stack, ML, and optimization

New York, NY0y exp
GeminiUniversity of Wisconsin–Madison

“Built a production-style PyTorch LSTM system that generates structured piano compositions from 1200+ MIDI files, then significantly improved long-range musical coherence by implementing Bahdanau attention based on research literature. Also has internship experience using Docker Compose for containerized backend workloads and has independently used Ray to scale ML experiments across multiple GPUs, including dealing with GPU scheduling/memory oversubscription issues.”

AlgorithmsAngularBashCC#C+++104
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AG

Anuj Garlapati

Screened

Junior Cloud/DevOps Engineer specializing in Kubernetes, Terraform, and multi-cloud customer engineering

New York, NY2y exp
SeqeraUniversity of Waterloo

“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.”

PythonBashSQLGoJavaScriptKubernetes+64
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