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Vetted Distributed Tracing Professionals
Pre-screened and vetted.
Junior Software Engineer specializing in backend, cloud, and AI-enabled enterprise systems
Executive CTO/VP Engineering specializing in high-performance AI, data systems, and distributed infrastructure
Sangeeth Kumar Mohan
Senior Lead Software Engineer specializing in authentication platforms and distributed systems
“Full-stack engineer (T-Mobile experience) focused on authentication/session-management systems, with hands-on work optimizing token-validation flows and reducing latency by eliminating redundant API calls and adding caching. Brings strong production ownership with observability (Splunk/Grafana), Postgres data modeling/index tuning, and resilient async workflow design (idempotency, retries/backoff, queues).”
Jugal Rayala
Mid-level Full-Stack Developer specializing in AI-powered cloud applications
“Full-stack engineer who has owned customer-facing AI recommendation and analytics dashboards end-to-end (backend APIs/data processing through React UI, deployment, and monitoring). Demonstrates strong systems thinking around scaling microservices—using observability, caching, async workflows, and resilience patterns—and also built an internal ops dashboard that became the default tool for on-call incident reviews.”
mahesh narne
Senior Full-Stack Software Engineer specializing in cloud-native microservices and web apps
“Backend-focused engineer building customer support/order-tracking platforms with Java 17/Spring Boot microservices and a React/TypeScript frontend. Deep experience running event-driven systems on Kubernetes (Kafka, Redis, MySQL) with strong observability (Prometheus/Grafana/Splunk), SLOs, and safe deployment practices (feature flags, canaries). Also built an internal monitoring/debugging dashboard that consolidated metrics and logs for on-call engineers and was adopted by other teams to speed incident response.”
Akash Patil
Mid-Level Software Engineer specializing in backend systems and LLM/RAG applications
“Backend/AI engineer at Intuit who built a production AI-powered case assistant for support agents (FastAPI on AWS EKS) combining Postgres case data, OpenSearch retrieval with embedding reranking, and internal LLMs. Improved peak-season reliability by diagnosing P95/P99 timeout spikes and cutting P95 latency from ~800ms to <400ms via composite indexing, keyset pagination, connection pool tuning, and caching, while adding grounded-generation guardrails (evidence packs, confidence thresholds, fallbacks, human-in-the-loop).”
Rahul Kushwaha
Mid-level Software Engineer specializing in FinTech and scalable microservices
“Backend/platform engineer focused on high-traffic financial systems, owning real-time event-driven ingestion and Kafka streaming pipelines using Python/FastAPI, Avro schemas, and AWS services. Has hands-on Kubernetes (EKS) and GitOps/CI-CD experience (ArgoCD/Jenkins) and supported large-scale migrations from legacy VMs to containerized microservices with zero/low-downtime cutovers.”
Mid-level Full-Stack Developer specializing in Python, React, and cloud-native AI microservices
Mid-level DevOps Engineer specializing in multi-cloud Kubernetes and CI/CD automation
Senior Full-Stack Engineer specializing in real-time Unity and scalable backend services
Senior .NET Full-Stack Engineer specializing in healthcare cloud platforms
Mid-level Software Engineer specializing in backend systems and LLM-powered AI applications
Mid-Level Backend Software Engineer specializing in distributed systems and observability
Senior Backend Engineer specializing in cloud-native microservices and secure APIs
Mid-level Backend/Data Engineer specializing in legal data pipelines and APIs
keerthana medaveni
Mid-Level AI/ML Software Engineer specializing in agentic LLM systems
“Built and deployed a production LLM-powered multi-agent compliance copilot (life sciences/finance) using LangChain/LangGraph + RAG over vector databases, delivered via async FastAPI on Kubernetes. Emphasizes audit-ready, deterministic outputs with schema constraints and citations, plus rigorous evaluation/monitoring; reports 60%+ reduction in manual research time and successful production adoption.”
Shreyansh Srivastava
Mid-Level Full-Stack Software Engineer specializing in API-first microservices and cloud platforms
“Backend-focused engineer who built a resume processing and job application platform using Python/MongoDB/Streamlit, including OpenAI-powered skill/keyword extraction and recruiter-facing search/filtering. Has hands-on cloud deployment experience on AWS/Azure and executed an on-prem reservation portal migration to Azure using a phased trial-and-cutover approach; also automated CI/CD with Jenkins and GitHub Actions.”