Vetted Observability Professionals

“Backend-focused engineer who uses AI tools pragmatically for rapid development while staying deeply attentive to concurrency, deadlocks, and system reliability. Built foundational AI retrieval architecture for MastadonTutorAI using ChromaDB and RAG pipelines, and is especially interested in applying multi-agent systems to automate complex backend testing and root-cause analysis.”

Siva Harini Sri Janaki Raman

Screened

Mid-level Data Engineer specializing in cloud data platforms

Dallas, TX3y exp

“Built an AI-powered internal support assistant at CVS Health using GPT-4, LangChain, and Pinecone, applying RAG, validation, and monitoring to reduce repetitive support tickets while protecting sensitive healthcare data. Stands out for a pragmatic approach to AI engineering: using multi-agent and LLM workflows to accelerate development while keeping systems constrained, observable, and production-friendly.”

“LLM/agentic systems practitioner who specializes in moving demo-only assistants into reliable, observable, cost-controlled production services. Strong in real-time diagnosis of complex agent workflows (including tracing, loop detection, and guardrails) and in customer-facing enablement—running workshops, building tailored PoCs, and partnering with sales to close deals by proving reliability in high-risk pilots.”

“Backend/platform engineer who has owned a Python/FastAPI results API and deployed it on Kubernetes with Helm and GitHub Actions-driven CI/CD. Demonstrates strong production operations mindset across performance tuning, monitoring, safe rollouts/rollbacks, and phased migrations, plus hands-on Kafka streaming experience focused on ordering and idempotency.”

Vineet Jujjavarapu

Screened

Mid-level Software Engineer specializing in cloud-native data platforms

College Park, MD3y exp

“Software engineer with hands-on experience using AI coding assistants and LangChain-based agent workflows in RAG/LLM projects. Stands out for combining practical multi-agent experimentation with strong grounding in system design, distributed systems, and production-minded validation of AI-generated outputs.”

Anudeep Eloori

Screened

Mid-level Software Developer specializing in full-stack enterprise applications

USA3y exp

“Software engineer with experience building and iterating high-volume Spring Boot microservices on AWS (Docker/Kubernetes) and integrating with React front-ends. Also delivered an LLM-powered document summarization system using embeddings + retrieval (RAG) with grounding/guardrails and built evaluation loops that directly drove retrieval and chunking improvements. Has scaled Kafka-based pipelines processing millions of messy financial/infrastructure records with reliability and cost/latency tradeoff management.”

Anuja Nayak

Screened

Junior Software Engineer specializing in distributed systems and reliability

Seattle, WA3y exp

“Oracle engineer focused on reliability and internal platform tooling, with hands-on experience automating regional traffic failover and building an LLM-assisted incident investigation workflow. Stands out for owning production-impacting systems end-to-end and delivering measurable operational gains, including cutting failover recovery to under five minutes and reducing incident triage from hours to minutes.”

Namratha Medaboina

Screened

Mid-level Software Engineer specializing in backend systems for healthcare and FinTech

3y exp

“Built Python-based clinical data processing workflows at CVS Health, automating ingestion, validation, transformation, and ML prediction across multiple healthcare systems. Stands out for combining AI-assisted development with rigorous human review, validation checkpoints, and production monitoring in regulated healthcare environments, including a reported ~26% efficiency improvement.”

Vik Krane

Screened

Director-level Product Leader specializing in AI-powered SaaS and FinTech

12y exp

“Product leader and startup co-founder who has been shipping AI-powered products since 2020 across creative tools, expert knowledge products, and financial compliance workflows. Particularly notable for building Shotcraft from zero to scale, using AI to turn scripts into executable shot lists, and for a nuanced human-centered AI philosophy that emphasizes user control over critical outputs.”

“Full-stack and AI product engineer focused on data instrumentation and tracking-plan automation. They built an end-to-end publish architecture plus an MCP/agent workflow that turns PRDs, Figma files, and meeting transcripts into tracking plans and implementation-ready code, reportedly shrinking work from 4-5 days to minutes. They also show strong judgment around productionizing LLM systems, with tool-centric prompt design, backend guardrails, and human-in-the-loop controls for high-risk actions.”

“Built internal product features at Sysco's Collab Cafe across React/TypeScript frontend and Spring Boot/PostgreSQL backend, including a full project invite flow and an early AI-style project matching capability. Stands out for owning features end-to-end, improving React dashboard performance with profiling and component refactoring, and making pragmatic 0→1 tradeoffs to ship quickly.”

Vinay K Naidu

Screened

Senior Full-Stack Engineer specializing in Healthcare IT and FinTech

5y exp

“Built and shipped a production LLM-powered incident assistant integrated with monitoring, logs, and metrics systems that reduced triage time by 30–40% and improved MTTR. Stands out for a strong reliability-first approach to agent design, including deterministic orchestration, strict schemas, fallback flows, grounding checks, and safeguards for messy operational data.”

“Series A startup engineer with broad full-stack ownership across backend, data, and frontend, including a real-time ingestion platform that scaled to 10x higher daily volume without downtime while cutting latency from minutes to seconds. Brings strong fintech and B2B SaaS experience building auditable, high-throughput systems for analysts, operations, and compliance teams in regulated environments.”

Jahid Hasan

Screened

Mid-level AI Product Leader specializing in agentic systems and developer platforms

Ames, IA4y exp

“Cofounder of Tometo AI who built a multi-agent engineering manager platform aimed at giving startup founders FAANG-style team visibility and blocker detection. Stands out for combining product leadership, AI evaluation rigor, and user-driven UX pivots, with tangible traction including a #2 Product Hunt launch and 150+ customers onboarded.”

Pallavi Thorat

Screened

Mid Software Engineer specializing in backend, cloud, and AI systems

USA, USA3y exp

“Front-end engineer with strong experience building sophisticated, data-heavy financial dashboards for finance analysts and business stakeholders. Stands out for combining React/Next.js architecture, D3.js visualization, and browser-level performance tuning to deliver measurable impact, including ~40% operational efficiency improvement and ~35% lower session drop-off.”

“Backend/platform engineer who has built and scaled production Java/Spring Boot + Kafka services on AWS/Kubernetes (1M+ msgs/day) and led reliability/performance fixes that restored SLAs (25–30% latency improvement; 99.9% uptime). Also shipped an AI customer-support chatbot end-to-end using retrieval + guardrails and rigorous evaluation/observability, improving resolution time 40% and satisfaction 25%, with a strong plan/execute/verify approach to agentic workflow reliability.”

“Enterprise platform engineering leader who identified platform engineering as a major opportunity at Kyndryl and built an entire internal practice around it by codifying the offering and evangelizing it across leadership. Now exploring founding an agentic AI developer platform aimed at reducing variance and improving consistency in building/deploying cloud-native applications; has not raised capital yet.”

“Verizon engineer who productionized an LLM-based personalization capability for a customer-facing digital platform, owning the path from success metrics through scalable APIs, A/B validation, and post-launch monitoring (latency/accuracy/drift). Experienced in diagnosing and fixing real-time LLM/RAG workflow issues under peak load, and in enabling adoption via tailored technical demos/workshops and sales support materials.”

“Backend/data engineer with hands-on production experience across Python REST APIs and PostgreSQL, plus AWS containerized deployments using CloudFormation, Jenkins CI/CD, and CloudWatch monitoring/autoscaling. Has built data validation/ETL-style workflows with schema/version checks and targeted reprocessing, modernized legacy batch processing into Java services with phased parallel migrations, and delivered measurable SQL performance gains (~50% query runtime reduction).”

“Backend engineer with experience at Razorpay and Groww, focused on hardening high-throughput financial systems for reliability and low tail latency through incremental improvements (SQL/index tuning, Redis caching, timeouts, idempotency). Also built/refactored a commodity risk tracker using Supabase Auth + Postgres RLS for strict per-user isolation, with a strong emphasis on API contracts, observability, and safe migrations.”

“Backend/data engineer with production experience building a SaaS analytics platform: FastAPI-based microservices with Redis caching and reliability patterns (RBAC, retries/backoff, centralized error handling). Also delivered AWS data pipelines (Glue/PySpark to Redshift) and owned real production incidents using CloudWatch/SNS, plus hands-on PostgreSQL query tuning on multi-million-row reporting workloads.”

“Backend engineer with experience evolving a real-time transaction and rewards processing platform from a tightly coupled architecture into domain-based microservices. Uses REST plus Kafka for synchronous vs. asynchronous workflows, and builds Python/FastAPI APIs with Pydantic contracts, Docker/Kubernetes deployments, and JWT/OAuth-based security; has also supported analytics/dashboard use cases (Power BI).”

“LLM/RAG engineer who took a PDF-heavy agent from prototype to production for an Africa-based client, combining Pinecone retrieval with robust PDF parsing (unstructured.io, OCR, structured table extraction). Demonstrates strong production mindset (eval metrics, prompt hardening, security/scalability) and measurable optimization impact (30% efficiency gain, 2x faster responses), and has helped close deals by building security-focused POCs for skeptical IT stakeholders.”