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Vetted Monitoring Professionals
Pre-screened and vetted.
Sriram Krishna
Mid-Level Software Engineer specializing in AI/ML and cloud-native platforms
“Backend/AI engineer who has built production LLM orchestration and agentic workflow systems in Python/FastAPI on Kubernetes across AWS/Azure. Demonstrated strong reliability engineering by debugging a real-world memory retention issue that caused latency spikes/timeouts, and strong data/performance chops with a PostgreSQL optimization that cut query latency from ~1.2s to ~15ms. Targets roles building scalable, guardrailed AI-driven workflow automation with robust observability and human-in-the-loop controls.”
Sree Manasa Vuppu
Mid-level AI Engineer specializing in Generative AI, LLMs, and RAG
“Internship at Discovery Education building a production LLM/RAG chatbot that let marketing and sales teams query and interpret Looker/BI dashboards in natural language, with responses grounded in compliance and state education standards. Emphasizes rigorous evaluation (faithfulness/precision/recall/latency) plus user-feedback analytics, and used LangChain for orchestration, chunking/context-window control, and integration with enterprise sources like SharePoint.”
Annie Suzan Edwin Arokiaraj Caroline
Junior Full-Stack Software Engineer specializing in distributed systems and data pipelines
“Backend engineer with hands-on experience building distributed data and API platforms (Kafka + Neo4j on Kubernetes), including processing 3M+ NYC taxi trip records and achieving sub-second graph analytics queries. Strong focus on reliability and performance in Python/FastAPI systems—async refactors, caching, timeouts/retries, feature-flagged rollouts, and JWT/RBAC security for production services.”
Samee Rauf
Junior AI/Full-Stack Software Engineer specializing in ad automation and LLM systems
“Full-stack engineer with deep ad-tech/marketing automation experience, building production tools that reduce programmatic ad waste and improve search ads performance. Shipped and operated AWS-deployed, Dockerized systems with Postgres/Redis and strong observability (Datadog/OpenTelemetry), and delivered measurable impact (25k campaigns processed, 50k sites negated, 3–4 hours/week saved). Built scalable abstractions for multi-platform ad integrations, enabling rapid onboarding of additional clients.”
Sanskar Pandey
Junior Full-Stack Java Developer specializing in FinTech microservices
“Full-stack engineer with production experience building a real-time order tracking system using React + Firebase/Firestore, emphasizing audit-friendly data modeling, state-machine-based status transitions, and strong post-launch ownership (performance, security rules, reliability). Demonstrated measurable frontend performance gains by isolating real-time updates to dynamic components and applying memoization, plus backend reliability patterns (idempotency, retries) and SQL query/index optimization validated with EXPLAIN ANALYZE.”
Abhiram Mullapudi
Mid-level ML Engineer specializing in real-time inference and anomaly detection
“Built DocMind, an end-to-end PDF chat assistant using React/TypeScript, FastAPI, and Postgres/pgvector, showing full-stack ownership plus practical performance tuning and AWS debugging skills. At Social Tech Labs, improved onboarding, shipped lean under ambiguity, and created a reusable low-latency feature serving layer that reduced duplicated infrastructure work across models.”
Mandar Sharadchandra Thengrey
Junior Software Engineer specializing in backend automation and AI-integrated systems
“FinTech engineer who has owned customer-facing onboarding deployments end-to-end, combining React/Node.js application development with workflow automation and post-launch operational metrics. They also implemented an LLM-driven onboarding assistant using contextual prompts and backend orchestration, and showed practical production experience debugging non-deterministic AI behavior caused by stale pipeline context.”
Viswanath Jagaluri
Mid-level Full-Stack & AI Engineer specializing in LLM applications
“Full-stack engineer who has shipped and operated generative-AI chat/QA features end-to-end, including a RAG-based pipeline with guardrails and cost/latency monitoring in production. Experienced with React/TypeScript + Node/Postgres architectures, Dockerized deployments to AWS (EC2) via GitHub Actions CI/CD, and building reliable ingestion/ETL systems with idempotency, backfills, and reconciliation.”
Baby Swathi Ramisetti
Mid-level Backend Software Engineer specializing in Python APIs and cloud-native systems
“Software/product engineer who owns customer-facing internal platforms end-to-end, with deep experience building data pipeline health and data quality tooling (near-real-time alerting and ops dashboards). Strong in React/TypeScript + Python REST architectures and microservices with RabbitMQ, emphasizing reliability patterns (idempotency, DLQs, correlation IDs) and fast, safe iteration via feature flags, testing, and observability.”
Shaktisharan Rajure
Mid-Level Full-Stack Engineer specializing in microservices and cloud APIs
“Software engineer who builds workflow-centric products end-to-end, including a customer-facing module on the Trident AI content platform and an internal content workflow tool adopted as the default process. Strong in TypeScript/React + FastAPI architectures and in scaling event-driven microservices with RabbitMQ, emphasizing reliability (idempotency, DLQs) and observability (correlation IDs) to reduce outages and debugging time.”
Idris Lawal
Senior DevOps Engineer specializing in cloud infrastructure, CI/CD, and Kubernetes
“Cloud/DevOps-focused engineer with hands-on experience building Azure DevOps CI/CD pipelines for containerized applications deployed to AKS, including security scanning, approvals, versioned artifacts, and rollback. Also implemented Terraform-based IaC for Azure (VNets/subnets/NSGs/AKS) with modular design, remote state/locking, and drift detection; resolved a real deployment outage caused by an Azure RBAC permission change.”
Brian Bonnell
Senior IT Infrastructure & Cloud Leader specializing in enterprise modernization
“Entrepreneurially minded technology-focused candidate who has built a full business plan (including business continuity planning) and successfully raised $65,000 by pitching to the SBA and angel investors. Identified a market gap in small businesses lacking IT staff and developed a remote IT support method to address it.”
Saideep Reddy Talusani
Mid-level Backend Engineer specializing in Python APIs and cloud-native services
“Data engineer with experience at Morgan Stanley and Star Health owning production-grade lakehouse pipelines for credit risk and healthcare datasets. Built Azure/Databricks/Delta/Snowflake-based platforms processing millions of records per day with strong data quality, observability (Monte Carlo/Azure Monitor), and reliability practices, plus experience delivering curated data services with performance tuning and backward-compatible versioning.”
Kevan Mehta
Junior Backend/Cloud Software Engineer specializing in microservices and cost-optimized AWS systems
“Built a production anomaly-detection workflow at VDOIT for messy cloud billing/cost data, emphasizing validation, idempotency, retries, and monitoring. Delivered measurable impact by preventing ~$50K/month in overspend and improving response time, and is now applying the same multi-step pipeline approach to LLM-based agent workflows.”
Manish Abburu
Mid-level Software Engineer specializing in data pipelines, web scraping, and APIs
“Backend/data engineer who has owned end-to-end production pipelines and data services, processing ~500K–1M records/day from APIs/logs into MySQL and serving via REST APIs. Strong focus on reliability and data quality (ELK + structured logging/monitoring), with measurable improvements (~30% reduction in bad data, ~20% query performance gains) and experience operating external data collection/scraping systems with anti-bot and schema-change resilience.”
Taruni Reddy Ampojwala
Mid-level GenAI Engineer specializing in LLM agents and RAG systems
“Built and deployed a production RAG-based LLM assistant that answers day-to-day operational questions from internal PDFs/SOPs, with strong emphasis on data consistency (metadata versioning, confidence thresholds, conflict handling) and low-latency retrieval at scale. Experienced designing and orchestrating multi-agent LLM workflows (retrieval/validation/generation) and pipeline orchestration for ingestion/embedding/vector-store updates, plus iterative delivery with non-technical operations/business stakeholders.”
sampath achalla
Mid-Level Software Engineer specializing in backend and full-stack web applications
“Backend engineer focused on scalable, secure, observable systems—built an async workflow backend with REST APIs and state persistence that improved reliability under concurrent load and cut end-to-end processing time ~40%. Strong in production security for multi-tenant systems (OAuth2/JWT, RBAC, DB row-level security) and in low-risk migrations using feature flags and canary releases, including catching and preventing cross-tenant data access issues with CI-based RLS tests.”
Srikar Tharala
Mid-level AI/ML Engineer specializing in Generative AI and RAG systems
“Currently at ProShare and reports building an AI/LLM-powered system deployed to production, aimed at helping with status-related difficulties and reducing misunderstandings across transactions. Also cites prior collaboration at Porsche with marketing teams, focusing on translating marketing goals into technical requirements and communicating solutions clearly to non-technical stakeholders.”
Atharva Chavan
Junior Full-Stack Software Engineer specializing in mobile, cloud, and GenAI integration
“Software engineering intern with hands-on ownership of a Java/Spring Boot order management microservice, including production performance tuning via Redis caching and database indexing driven by API logs/metrics. Also contributed to a production mobile-backend LLM feature using RAG with embeddings over structured data and documents (DB + object storage), with guardrails to keep responses grounded.”
Sampath Achalla
Mid-level Python Full-Stack Engineer specializing in AI microservices and cloud data platforms
“Backend-leaning full-stack engineer in fintech/payments who shipped an end-to-end Stripe payments + webhook system for a financial microservices platform, emphasizing ledger accuracy via idempotency, transactional writes, retries, and DLQs. Also delivered a real-time React/TypeScript payment status dashboard informed by user interviews, and improved production performance by 35% p95 latency through PostgreSQL tuning and Redis caching on AWS.”
William Watanabe
Mid-level Full-Stack Software Engineer specializing in authentication and SolidJS/TypeScript
“Mid-level full-stack engineer (Los Angeles) who built and shipped an end-to-end authentication system for SolidAuth, an open-source SolidStart ecosystem library published to NPM with 1000+ downloads. Experienced designing React/TypeScript + Node + Postgres architectures, operating lightweight production systems on AWS (EC2/S3/RDS/IAM/CloudWatch), and building resilient third-party ingestion/integration flows with idempotency, retries, queues, and backfills; also worked in an early-stage NIL startup (OFFSZN) shipping core onboarding/profile features amid changing requirements.”
Shuchi Shah
Senior Software Engineer specializing in Backend Systems and Generative AI (RAG)
“Backend engineer with experience building an end-to-end civic tech AI platform that ingests city council meeting videos, transcribes them with Whisper, and enables natural-language Q&A via a LangChain/FAISS RAG pipeline. Demonstrated strong systems thinking by tuning retrieval for accuracy/latency/memory (cutting response time ~3s→1s and memory ~500MB→25MB) and by safely migrating an ERP from monolith toward services using dual writes, reconciliation, and idempotency to protect financial workflows.”
Avanishika Revelli
Junior Software Engineer specializing in backend, cloud, and robotics automation
“Graduate Research Assistant in Robotics at Arizona State University who built an end-to-end LLM-driven task execution framework enabling collaborative robots to convert high-level natural language instructions into safe, executable ROS actions. Implemented robust monitoring, failure detection, and automatic replanning, and addressed real-world issues like timestamp/frame-transform mismatches and heterogeneous robot interoperability using adapter nodes.”
Atharva Bibave
Entry-level Full-Stack Software Engineer specializing in backend, cloud, and AI systems
“Software engineer with hands-on experience across platform modernization, production AI agents, and workflow automation. They led a monolith-to-microservices migration that increased deployment speed from weekly to daily, built a self-healing GPT-powered browser agent with an 85% autonomous recovery rate, and founded/ran ZapDash, where they hardened Kafka-based integrations against silent data loss.”