Vetted Datadog Professionals

“Backend/platform engineer with production ownership of high-volume transaction analytics and fraud monitoring services built in Java/Spring Boot. Has scaled data processing platforms (including healthcare datasets) and operated Kafka-based event pipelines with schema versioning, deduplication, and replay/backfill workflows, using strong observability via CloudWatch/Grafana and CI/CD with Jenkins.”

Lucas Silbernagel

Screened

Senior Front-End Software Engineer specializing in accessible, high-performance web apps

Toronto, Canada6y exp

“Frontend engineer who led the 2025 end-to-end launch of the Score Casino web platform, integrating a new regulated brand into an existing monorepo with scalable theming, Next.js routing changes, and supporting Docker/SRE deployment work. Emphasizes quality at scale through visual regression testing, Datadog/Bugsnag observability, and test-suite redesign (parameterized theme tests) that reduced CI flakiness; shipped the launch two months ahead of schedule while meeting GLI submission standards.”

Rasika Deodhar

Screened

Mid-level Full-Stack Software Engineer specializing in Generative AI

Dublin, Ireland6y exp

“Full-stack engineer who shipped an end-to-end speech capability for an LLM chatbot UI, integrating OpenAI APIs and publishing via Google Apigee with client documentation. Has experience operating deployments with Jenkins/Kubernetes/Docker and monitoring with Datadog, and has worked in an innovation-center environment building rapid prototypes under ambiguity with tight stakeholder feedback loops.”

“AI/LLM engineer who built a production content-generation system for nursing education, combining multimodal RAG over proprietary PDFs (including images) with structured Cosmos DB data and external sources. Strong focus on production reliability—prompt-chaining with LangChain, validation/guardrails, and Azure-based monitoring/observability—plus experience designing Azure AI agents with tool integrations like Bing Search.”

“LLM/ML platform engineer with hands-on experience taking an LLM document summarization prototype into a production-grade service on AWS EKS, emphasizing low-latency inference, drift monitoring, and safe CI/CD rollouts (canary + rollback). Strong in real-time debugging of agentic/RAG systems (tracing, retrieval/index drift fixes) and in developer enablement through practical workshops (Docker/Kubernetes/FastAPI) plus pre-sales support via demos and benchmarks to close pilots.”

Tuukka Luolamo

Screened

Executive Technology Leader (CTO) specializing in AI, cloud, and distributed platforms

Remote14y exp

“Engineering leader who stays hands-on in high-leverage technical areas (architecture, scalability, reliability) while operating at an executive level. Led StagePilot’s shift from a tightly coupled legacy system to a cloud-native, event-driven real-time platform proven at 1M+ concurrent users, and previously scaled multiple SRE teams at McGraw-Hill with SLOs, on-call, and blameless ops practices.”

Narendra R

Screened

Senior Full-Stack Java Developer specializing in microservices and cloud platforms

Dallas, TX7y exp

“Backend engineer focused on scalable Python/Flask services and high-performance PostgreSQL/SQLAlchemy systems, with demonstrated wins like reducing N+1-driven response times to under 200ms and cutting P95 latency below 1s via background queues and caching. Has production experience operationalizing ML models as Dockerized APIs on AWS (S3/Lambda) with monitoring (CloudWatch/ELK), plus robust multi-tenant isolation using JWT-driven tenant context and row-level security.”

Rohit Vibhu Channananjundarya

Screened

Mid-level Software Engineer specializing in distributed systems and full-stack platforms

Chicago, IL6y exp

“Engineer who treats AI as a force multiplier rather than a replacement for judgment, with hands-on experience using tools like Claude Code, Cursor, Copilot, and Codex across planning, coding, testing, and review. Particularly notable for building a multi-agent PR review system that automated summarization, risk scanning, schema validation, and test suggestions, helping the team shift reviewer time toward architecture and business logic.”

“Customer-facing technical professional with experience supporting LLM/agentic-style workflows and complex integrated systems (APIs, backend logic, databases). Partnered with sales/customer teams at Radix Health to onboard new clients in phased prototypes, translating non-technical requirements into technical scope and implementing core product changes to tailor the appointment-booking solution for providers.”

“Full-stack engineer with hands-on experience building a large-scale healthcare claims and provider-enrollment system end-to-end (React frontend, Spring Boot microservices, PostgreSQL on AWS). Optimized high-volume claims processing (millions of records/day) using indexing/pagination and asynchronous workloads via AWS Lambda/Kafka, and deployed containerized services with Docker/Jenkins on AWS.”

“Software engineer who owned end-to-end delivery of customer-facing agricultural forecast reporting (crop yield/health) and iterated quickly via rigorous edge-case testing and customer feedback. Also built an internal ML training platform (TypeScript/React + Flask/Python + MongoDB) used by every developer, with architecture designed to stay responsive under heavy compute load.”

“Maintained and improved a set of JavaScript packages at JPMorgan, including a major refactor of an event-emission layer used in LLM streaming that delivered ~20% runtime speedup with no API changes. Known for a measurement-driven performance approach (profiling + simplification + validation), strong backward-compatibility discipline, and documentation that accelerates internal adoption and reduces support questions.”

Navindu Jayatilake

Screened

DevOps Technical Lead specializing in Kubernetes, AWS, and platform engineering

Colombo, Sri Lanka6y exp

“Sri Lanka–based DevOps/Platform engineer focused on Kubernetes and AWS who has led real production incidents and recoveries (network-policy-induced asymmetric routing; node pool failure due to CNI upgrade). Built production CI/CD with GitHub Actions (ephemeral self-hosted runners on EKS), ArgoCD, Vault, and Terraform, and led a phased ECS-to-EKS migration including Kafka consumers and MongoDB Atlas private endpoints.”

Hadi Jaffery

Screened

Junior Data Engineer specializing in Snowflake and investment data platforms

Boston, MA3y exp

“Private markets/private credit data engineer owning core Snowflake/AWS data infrastructure (S3 → ActiveBatch → Snowflake) with automated iceDQ quality checks and curated datasets for internal Power BI/React reporting. Drove major reliability and delivery improvements, including cutting DB CI/CD deploy time 50% and reducing downstream table errors by 90%+, and also built an internal React/FastAPI app to visualize the team’s data infrastructure in an ambiguous early-stage environment.”

Sreelekha Vuppala

Screened

Mid-level Data Scientist specializing in Generative AI, MLOps, and cloud data platforms

USA4y exp

“GenAI/ML engineer (CitiusTech) who has deployed production RAG systems for compliance/operations document Q&A, using Pinecone + FastAPI microservices on Kubernetes with strong monitoring and guardrails. Also built a GenAI-powered incident triage/routing solution in collaboration with non-technical stakeholders, achieving 35% faster response times and 40% fewer misclassified tickets, and has hands-on orchestration experience with Airflow and AutoSys.”

“Marketing analytics candidate with experience at WPP and on a global Coca-Cola campaign, focused on turning messy multi-platform media data into trusted reporting and decision systems. They combine hands-on SQL/Python pipeline building with stakeholder KPI alignment, and cite a 22% improvement in media effectiveness plus faster budget reallocation through daily automated reporting.”

“Candidate appears to work at the intersection of enterprise billing/payments systems and AI-powered support automation. They describe owning customer deployments, integrating PayPal/Stripe, building LLM/RAG workflows for finance operations, and handling production incidents affecting millions of invoice events with measurable improvements in resolution time and ticket volume.”

“Full-stack engineer with 6+ years of experience building high-scale internal products and AI-powered workflows, including a U.S. Bank payment operations dashboard handling 500k+ transactions and real-time analyst collaboration. Stands out for true end-to-end ownership—from React/TypeScript frontend architecture to Node/Spring services, PostgreSQL/Redis optimization, Kubernetes deployment, and Datadog monitoring—plus measurable impact on adoption, latency, and analyst efficiency.”

Supreet Purthpli

Screened

Mid-level AI/ML Software Engineer specializing in cloud-native MLOps and FinTech

San Francisco, CA4y exp

“Software engineer with JPMorgan Chase experience delivering end-to-end fintech features (Next.js/React/Node/Postgres on AWS) and measurable performance gains. Built and productionized an AI-native credit decisioning workflow combining LLMs, vector retrieval, and a rules engine with strong governance (bias checks, auditability, human-in-loop), improving precision and cutting underwriting turnaround time by 40%.”

“Backend engineer who designed and evolved an AWS-based event-processing system in Python/PostgreSQL, achieving a 60% p95 latency reduction while improving reliability during traffic spikes. Led a zero-downtime migration from a monolithic Django app to FastAPI microservices using feature flags, strong testing, and cross-team coordination, with production-grade observability (Prometheus/Grafana/CloudWatch) and security (JWT/OAuth2, RBAC, Postgres RLS).”

“Backend/data engineer who builds production FastAPI microservices and AWS serverless/Glue pipelines for SMS analytics and marketing segmentation. Led a legacy batch modernization into modular services (FastAPI + Glue/Athena + ClickHouse) using shadow-mode parity checks, feature flags, and incremental rollout. Demonstrated measurable performance wins (12s to sub-second SQL; ~40% CPU reduction) and strong incident ownership with proactive schema-drift prevention.”

“Data engineer focused on building reliable, production-grade pipelines and external data collection systems on AWS (S3/Lambda/SQS/Glue/EMR) using PySpark/SQL, serving curated datasets to Snowflake/Redshift for finance and fraud teams. Has operated a large-scale crawler ingesting millions of records/day with anti-bot tactics, schema versioning/quarantine, and CloudWatch/Datadog monitoring, and also shipped a versioned REST API with caching and query optimization.”

Keerthi Kalluri

Screened

Senior Full-Stack & GenAI Engineer specializing in healthcare and financial services

6y exp

“Built and deployed a production LLM-powered customer support assistant using a RAG backend in Python, focused on deflecting repetitive Tier-1 tickets and reducing resolution time. Demonstrates strong production engineering instincts around reliability (confidence scoring + human fallback), scalability/cost optimization (multi-stage pipelines), and workflow orchestration/observability (LangChain, custom DAGs, structured logging, step metrics).”

“Backend engineer with healthcare and financial services experience (Humana, PNC) who owned production-grade, high-volume ingestion-to-API pipelines end-to-end in C#/.NET and SQL. Strong focus on data quality, handling out-of-order/partial upstream records, and improving reliability/observability via structured logging and telemetry, plus significant SQL performance tuning to reduce peak-load issues.”