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Vetted Agile Professionals
Pre-screened and vetted.
Sahana Mudduluru
Mid-level Full-Stack Engineer specializing in cloud-native FinTech analytics
“Full-stack/ML-leaning engineer who has shipped production-grade real-time analytics and an internal AI support assistant using RAG over enterprise documentation. Demonstrates strong systems thinking across scalability, reliability, observability, and LLM safety/evaluation (thresholded retrieval, RBAC, response validation, regression-gated evals), with concrete iteration based on performance metrics and user feedback.”
Jaideep Janapati
Mid-level Data Engineer specializing in cloud data platforms and real-time pipelines
“Data engineer who has owned production pipelines end-to-end—from Kafka/Airflow ingestion through SQL/Python validation and dbt transformations into Redshift/BI. Also built and operated a large-scale distributed web scraping platform (50–100 sites daily, ~5–10M records/day) with Kubernetes, Kafka queues, robust retries/DLQ, anti-bot measures, and backfill-safe raw HTML storage.”
Hammad Ur Rahman
Senior DevOps Engineer specializing in cloud infrastructure and CI/CD
“IBM Power/AIX engineer who has owned a 150+ LPAR AIX 7.x estate with VIOS/HMC/vHMC and PowerHA in production, including real outage and failover recoveries. Also brings modern DevOps/IaC experience—built Jenkins pipelines deploying to AKS and implemented Terraform on AWS with remote state, locking, and drift management.”
Muhammad Mufti Aziz
Mid-level Product & QA Specialist specializing in FinTech payments and growth
“QA tester with console game experience across PlayStation/Xbox/Nintendo, focused on online multiplayer stability and monetization/reward flows, with pre-launch defect prevention. Brings a regulated fintech compliance-testing background and applies structured triage, SQL-based server/client validation, and AI-assisted workflows to accelerate coverage and debugging.”
Nagendra Reddy Palugulla
Mid-level Machine Learning Engineer specializing in LLMs, RAG, and MLOps
“Built and shipped a production real-time content moderation platform for Zoom/WebEx-style meetings, combining Whisper speech-to-text with fast NLP classifiers and REST APIs to flag hate speech, bias, and HIPAA-related content under strict latency constraints. Demonstrates strong MLOps/infra depth (Airflow, Kubernetes, Terraform/Helm, observability) and a pragmatic approach to reducing false positives via threshold tuning, context validation, and hard-negative data—while partnering closely with compliance and product stakeholders.”
Ryan Perera
Junior Front-End Developer specializing in React and accessible UI
“Frontend engineer who led end-to-end architecture for a warehouse management platform, emphasizing reusable domain-based React components and API-driven performance at scale (including barcode-scanning workflows). Also delivered a production-ready React Native iOS networking app MVP in ~5 weeks and built a data-driven React+TypeScript dashboard for collectible card market decisioning.”
Jyothsna V
Mid-level Backend Software Engineer specializing in Python/FastAPI and cloud-native microservices
“Backend engineer who evolved Coca-Cola bottlers' Trade Promotion Optimization platform at Coke One North America, building domain-focused microservices in Node.js and Python (Flask/FastAPI) with PostgreSQL. Experienced in multi-tenant security (OAuth2/JWT, RBAC, row-level scoping by bottler/region), API contract/versioning discipline, and Azure DevOps-driven incremental rollouts with strong observability.”
Ali Zafar Zaidi
Senior Frontend/Full-Stack Developer specializing in React and Next.js
“Frontend engineer who has led architecture and delivery of large, data-driven React/TypeScript interfaces used by thousands of users, with strong emphasis on scalable structure, performance, and automated quality gates (CI/CD, Jest/Cypress). Recently building a resume screening application for McMaster University students and has experience shipping role-based (RBAC) features with tight cross-functional collaboration and PR-based QA deployments.”
Satish Kumar Reddy
Mid-level AI/ML Engineer specializing in NLP, computer vision, and MLOps
“Built and deployed a production LLM/RAG intelligent document understanding platform for healthcare clinical documents (notes, discharge summaries, diagnostic reports), integrating spaCy entity extraction, Pinecone vector search, and a Spring Boot API on AWS with monitoring and guardrails. Demonstrates strong MLOps/orchestration (LangChain, Airflow, Kubeflow/Kubernetes) and a metrics-driven evaluation approach, and partnered with a healthcare operations manager to cut manual review time by 80%.”
Jasdeep Gill
Mid-Level Software Engineer specializing in AI and web development
“Built an OCR backend that trains a custom Tesseract model for proprietary fonts and scales via multi-tenant isolation (tenant-scoped APIs, per-tenant storage, JWT+RBAC). Improved high-load image processing by shifting OCR to async worker queues and adding Redis caching, cutting processing time by ~66%, and also integrated Claude API to auto-generate test cases on code changes.”
chandankumar ramamurthy
Junior Full-Stack Engineer specializing in LLM-powered products
“Built multiple systems from scratch at DSSD and Aglint, including an NGO sustainability reporting dashboard and a production LLM-powered phone screening agent using Twilio/Retell AI with RAG grounded in PostgreSQL candidate/job data. Strong focus on real-world reliability: guardrails, monitoring, and lightweight eval/regression loops that reduced recruiter score overrides by ~30%. Currently on OPT through May 2026 (plans STEM OPT extension) and committed to relocating to NYC for in-person work; seeking $90k–$120k base with meaningful equity for founding engineer roles.”
Shiva Dasi
Mid-level Software Engineer specializing in LLM agents and cloud-native systems
“Built and shipped production LLM agents in compliance-sensitive environments (FERPA), emphasizing reliability via structured outputs, state-graph orchestration (LangGraph), and CI-driven eval/regression testing. Also has experience hardening messy ERP ingestion pipelines at scale (50K monthly orders) with normalization, idempotency/deduplication, and robust failure handling using AWS (SQS/CloudWatch) and PostgreSQL.”
Yash Amre
Intern Data Scientist specializing in machine learning and NLP
“Analytics-focused early-career candidate with internship experience owning reporting and system performance analysis projects end to end. They combine SQL data preparation, Python automation, and dashboard delivery with measurable impact, including roughly 50% less manual reporting and about 20% better forecast accuracy.”
Charles Shaw
Executive technology leader specializing in AI, cloud transformation, and data platforms
“Candidate is targeting a CTO Venture Studio role and positions themself as a technical partner to founders rather than a founder personally. They demonstrate strong fluency in early-stage startup evaluation, especially around validating whether a product truly tests the business hypothesis and whether the underlying technology can scale significantly.”
Rahul Teggi
Junior Backend Software Engineer specializing in scalable APIs and cloud systems
“Full-stack product engineer focused on data-heavy dashboard applications, with hands-on ownership from React/TypeScript UI through Node/Express APIs to Postgres schema design and optimization. Stands out for combining product sense with engineering rigor: improving onboarding and reporting flows using analytics and user feedback, while also building reusable upload infrastructure and safe multi-tenant configurable experiences.”
Srihari Varadarajan
Senior Customer Success and Engineering Support specialist in enterprise software and monitoring
“Senior engineer with experience at Micro Focus/HPE (now OpenText) supporting enterprise customers on monitoring platform deployments, upgrades, and ongoing product use. Brings hands-on expertise in operations agents, agentless integrations, security-related upgrade troubleshooting, and cross-functional escalation with engineering to keep customer environments stable and successful.”
Manoj Panchakarla
Mid-level Data Engineer specializing in FinTech data platforms
“Backend-focused engineer with experience at Ramp, Easebuzz, and George Mason University, spanning data pipelines, workflow automation, and production reliability. Stands out for quantifiable performance gains, strong debugging instincts in distributed job systems, and translating ambiguous finance operations processes into measurable automation outcomes.”
Venkata Sai Niranjan Nadipineni
Senior Salesforce Developer specializing in Lightning and enterprise CRM
“Salesforce-focused candidate with hands-on ownership of end-to-end Service Cloud automation, including Apex schedulable jobs for inactive portal user tracking, warning notifications, deactivation, and reporting. Demonstrates strong architectural judgment across Apex, LWC, and Aura, with particular strength in scalable design, performance optimization, and rigorous testing/debugging in complex Salesforce environments.”
Mrudula Devaguptapu
Mid-level Software Engineer specializing in AI and backend systems
“AI/automation-focused implementation engineer who has owned customer-facing LLM deployments end-to-end, spanning support automation, lead outreach, and messy document-processing workflows. Stands out for combining hands-on technical depth in Python/OpenAI/RAG systems with measurable business impact, including cutting support resolution time from 24 hours to 6 hours and reducing manual outreach work by 60%.”
“Software candidate with hands-on experience using AI as a productivity multiplier across architecture, refactoring, testing, and code review. Has worked with LangChain-based multi-agent workflows to decompose complex engineering tasks for parallel execution, showing practical familiarity with emerging AI-native development patterns.”
Daksh Bhuva
Mid-level Software Developer specializing in full-stack web and mobile applications
“Engineer with hands-on experience modernizing healthcare platform authorization and EVV compliance workflows, including replacing hardcoded permissions with a Cerbos-based RBAC/ABAC system. Stands out for pragmatic AI-assisted development in regulated environments, with a strong emphasis on testing, auditability, and catching subtle business-rule failures before production.”
“Full-stack AI engineer focused on operational and healthcare analytics use cases, with hands-on experience building React/TypeScript frontends and Node/FastAPI/Flask backends for agentic systems. Stands out for combining LLM orchestration, retrieval grounding, and human-in-the-loop controls with measurable business impact, including a fraud detection dashboard that achieved 92% accuracy and cut manual review time by 85%.”
Samhitha Muvva
Mid-level Full-Stack AI Engineer specializing in agentic systems
“At ReferU.AI, designed and deployed an agentic RAG pipeline that automates multi-jurisdiction legal document drafting, emphasizing hallucination reduction through hybrid retrieval, validation agents, guardrails, and iterative regeneration. Experienced with orchestration frameworks (especially CrewAI) and rigorous testing/evaluation practices including human-in-the-loop review, adversarial testing, and production metrics/logging.”