Vetted Observability Professionals

Pre-screened and vetted.

Nithin Reddy - Mid-Level Software Development Engineer specializing in distributed systems and event-driven architectures in Santa Clara, California

Nithin Reddy

Screened

Mid-Level Software Development Engineer specializing in distributed systems and event-driven architectures

Santa Clara, California4y exp
Goldman SachsCentral Michigan University

Built and maintained an internal JavaScript/React real-time event monitoring UI used by multiple Goldman Sachs teams (e.g., Private Wealth Management and Bulk Trading Systems). Focused on scaling performance under hundreds of events/sec—using profiling, memoization, batching, and debouncing—and paired it with strong internal documentation and disciplined incident diagnosis via synthetic load testing and logs/metrics.

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PC

Pranit Chetta

Screened

Senior Full-Stack Java Engineer specializing in cloud-native AI and enterprise platforms

Wilmington, DE11y exp
JPMorgan ChaseGujarat Technological University

Full-stack product engineer who owned a live-events digital ticketing platform end-to-end, including blockchain-based ticket validation and high-traffic booking flows. Stands out for combining Angular/React frontend work with Java/Spring Boot backend architecture, plus strong production reliability practices around concurrency control, queues, observability, and UX optimization.

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JK

Mid-level AI/ML Engineer specializing in conversational AI, NLP, and LLM-powered RAG systems

Jersey City, NJ5y exp
JPMorgan ChaseSaint Peter's University
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VR

Mid-Level Software Engineer specializing in Java/Spring Boot microservices and cloud DevOps

NJ, USA5y exp
Goldman SachsStevens Institute of Technology
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SS

Senior DevOps Engineer specializing in multi-cloud infrastructure and Kubernetes

7y exp
KrogerUniversity of Dayton
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DJ

Devon Johnson

Screened ReferencesStrong rec.

Executive Cybersecurity & Infrastructure Architect specializing in incident response and resilience

Nashville, TN19y exp
Ceyepher SecurityAustin Peay State University

Founder of pre-revenue cybersecurity startup Ceyepher Security; has already set up lead-intent sourcing, automated pipeline/CRM analytics, and outbound marketing. Plans to raise capital after landing first clients to demonstrate value via revenue, whitepapers, and customer testimonials; interested in studio support to accelerate sales. Mentions a disability that has enabled significant time honing computer science skills and is open to joining innovative work even outside their own company.

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SA

Sharath Addepalli

Screened ReferencesStrong rec.

Mid-Level Software Engineer specializing in Python microservices and scalable web APIs

Franklin, TN3y exp
NissanUniversity of Florida

Backend engineer who replaced an Excel-heavy forecasting workflow with a secure, auditable FastAPI system (React UI + relational model + async workers), emphasizing deterministic processing, idempotency, and versioned ledger-style ingestion. Led a monolith-to-FastAPI migration at Bounteous using a strangler approach, feature-flagged incremental rollout, and data reconciliation/shadow-compare to protect integrity while scaling onboarding workflows.

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Vaishnavi Kashyap - Junior Full-Stack Software Engineer specializing in web platforms and sustainability analytics

Vaishnavi Kashyap

Screened ReferencesStrong rec.

Junior Full-Stack Software Engineer specializing in web platforms and sustainability analytics

1y exp
Saint-GobainUniversity of Massachusetts Amherst

Full-stack/backend engineer who owned a production digital assembly planning platform at Saint Gobain end-to-end (React/Node/Postgres), maintaining 99.9% uptime across 5 factory sites and driving a reported 90% improvement in factory-floor coordination. Also built and operated BigQuery + Vertex AI (ARIMA) forecasting/data pipelines processing 1M+ datapoints daily, with strong emphasis on idempotency and data-quality validation to prevent incorrect outputs.

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Lavrenti DeLavrenti - Director-level Technology Leader specializing in cloud-native platforms, AI/ML, and SaaS in Remote

Lavrenti DeLavrenti

Screened ReferencesStrong rec.

Director-level Technology Leader specializing in cloud-native platforms, AI/ML, and SaaS

Remote15y exp
Alioni Tech LabsGeorgian Technical University

Engineering leader (Director/VP level) who has repeatedly aligned product and engineering through ROI-driven quarterly roadmaps and strong stakeholder communication, including board presentations. Built a parallel cloud team to migrate an on-prem product to the cloud, credited with delivering $9M ARR, and led a Python monolith-to-serverless event-driven microservices transformation. Currently manages distributed teams across Mexico, India, and the US using pod-based structures, clear KPIs, and a supportive accountability culture.

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suparshwa patil - Mid-level Software Engineer specializing in AI platforms and full-stack systems in Santa Clara, CA

suparshwa patil

Screened ReferencesStrong rec.

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

Santa Clara, CA4y exp
One CommunityPurdue University

Built and shipped a production AI-powered Q&A/RAG onboarding assistant at One Community Global that unified knowledge across Notion, Google Docs, and Slack, cutting volunteer onboarding time by 45%. Demonstrates strong end-to-end ownership: LangChain agent orchestration integrated into a FastAPI backend, rigorous evaluation (200-query dataset, ~85% accuracy), and production feedback/monitoring with source-attributed answers to build user trust.

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VV

Vaishnavi Veerkumar

Screened ReferencesStrong rec.

Mid-level AI Engineer specializing in GenAI and RAG systems

Boston, MA4y exp
VizitNortheastern University

AI engineer who built a production e-commerce system that analyzes product images alongside sales and demographic data to generate actionable creative recommendations, now used by 20+ clients. Also built orchestrated document/agent pipelines (Airflow, LangGraph) including a compliance drift detector auditing 401 compliance documents, with an emphasis on traceability, logging, and production integration.

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LV

Mid-level Software Engineer specializing in SRE, observability, and LLM-powered automation

Richardson, TX2y exp
CiscoWestcliff University
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RS

Mid-level Software Engineer specializing in AI backend and FinTech

Syracuse, NY3y exp
Morgan StanleySyracuse University
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Manasa Pantra - Junior Software Engineer specializing in AI, LLM systems, and full-stack development in Stony Brook, NY

Manasa Pantra

Screened ReferencesStrong rec.

Junior Software Engineer specializing in AI, LLM systems, and full-stack development

Stony Brook, NY2y exp
Stony Brook UniversityStony Brook University

Product-focused full-stack engineer at startup (Zippy) who shipped a production multi-agent AI system for restaurant operations plus payments workflows. Built end-to-end: RAG grounded on a Notion knowledge base, structured function-calling task routing, FastAPI/JWT multi-tenant backend, and a polished React+TypeScript owner dashboard. Has real production incident experience (duplicate Stripe webhooks) and reports ~94% task-routing accuracy under load.

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AA

Abnik Ahilasamy

Screened ReferencesModerate rec.

Intern LLM/GenAI Engineer specializing in RAG, agentic systems, and low-latency inference

Chennai, India0y exp
Larsen & ToubroArizona State University

Interned at Larsen & Toubro where they built and deployed an agentic RAG document question-answering system to reduce time spent searching documents and improve trustworthiness. Implemented ReAct-style multi-step orchestration with LangChain/LlamaIndex plus evidence-bounded generation, grounding/citations, and rigorous evaluation—cutting latency ~40%, hallucinations ~35%, and unsafe outputs ~40% while collaborating closely with non-technical business/ops stakeholders.

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CD

Executive DevOps & Platform Engineering Leader specializing in cloud, SRE, and DevSecOps

Remote12y exp
Enel XNortheastern University

Fintech startup veteran (8+ years) building TrustRelay, a control-plane product between ERPs and banks to verify vendors, enforce pre-flight payout policies, automate reconciliation, and produce deterministic audit evidence. Currently at MVP stage and planning to pursue Founders Institute Boston Sprint 2026 while lining up design partners and raising pre-seed/seed.

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UG

Utkarsh Gogna

Screened

Mid-level Full-Stack Software Engineer specializing in Java microservices and cloud-native systems

Boston, MA5y exp
CGINortheastern University

Backend engineer with experience building and modernizing high-volume healthcare transaction systems, including migrating Java services to Spring Boot microservices and adopting Kafka-based event-driven architectures. Strong focus on production reliability and operability (observability, CI/CD, standardized patterns) plus security (OAuth/JWT, RBAC, Postgres/Supabase RLS) and resilient stream processing (idempotency, DLQs).

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JE

Jenna Emerman

Screened

Mid-Level Full-Stack Engineer specializing in MarTech and web experimentation

Remote5y exp
MailchimpVanArts (Vancouver Institute of Media Arts)

Frontend engineer at Mailchimp who leads end-to-end React/TypeScript features on the in-app homepage, including onboarding and campaign discovery components. Demonstrated measurable performance impact by cutting homepage LCP by ~2.5s and successfully shipped a major feature on an accelerated deadline using structured QA and staged rollout.

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SP

Soham Patel

Screened

Mid-level Machine Learning Engineer specializing in healthcare NLP and MLOps

Piscataway, NJ3y exp
Syneos HealthRutgers University - New Brunswick

ML/AI practitioner in healthcare (Syneos Health) who has deployed production clinical NLP and risk models. Built a BERT-based physician-note information extraction system on Docker + AWS SageMaker (reported ~42% retrieval improvement) and automated retraining/deployment with Airflow and drift detection, while partnering closely with clinicians to drive adoption (reported ~18% readmission reduction).

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VK

Vamsi Koppala

Screened

Mid-level Machine Learning Engineer specializing in Generative AI and RAG systems

Barrington, IL4y exp
ComericaTexas Tech University

LLM/ML engineer who has shipped an enterprise RAG-based Q&A system (LangChain/LlamaIndex, FAISS + Azure Cognitive Search, GPT-3.5/4 via OpenAI/Azure OpenAI) to production on Docker + Kubernetes/OpenShift, tackling hallucinations, retrieval quality, latency/cost, and RBAC/IAM security. Also partnered with operations leaders to turn manual reporting into an LLM-powered summarization and forecasting dashboard driven by real KPIs and iterative stakeholder feedback.

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HS

Mid-level Full-Stack Software Engineer specializing in cloud-native microservices

California, USA4y exp
OracleCalifornia State University, Long Beach

Cloud-native integration engineer (Oracle/OCI) with strong production deployment and incident-response experience, including API gateway rollouts, observability (Prometheus/Grafana), and multi-layer debugging for payments systems. Built Python/FastAPI microservices and automation for customer-specific reporting and data sync, and has delivered major performance gains (45 min to <10) plus reliability improvements (MTTD reduced 40%+) through monitoring, playbooks, and resilient integration patterns (streaming/queuing, retries, secure tokens, VPC peering).

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PK

Parth Kasat

Screened

Mid-level Forward Deployed Engineer specializing in AI automation for finance and data platforms

Remote2y exp
ArganoGeorge Washington University

LLM/agentic workflow specialist with healthcare deployment experience who has taken LLM-based automation from prototype to production using operator-in-the-loop validation, RAG-style retrieval, RBAC, and monitoring for sensitive data compliance. Demonstrated real-time incident resolution (retrieval timeouts due to network/proxy misconfig) and strong GTM support—hands-on developer workshops and sales demos translating technical safeguards and real-time ETL into measurable ROI (70% ops reduction, ~$200K/year savings).

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BA

Mid-level Solutions Architect / Full-Stack Developer specializing in LLM-enabled applications

MA, USA5y exp
MassMutualClark University

LLM/agentic systems practitioner focused on taking customer prototypes to production by hardening reliability (APIs, monitoring, security) and adding guardrails, evals, and incremental rollouts. Experienced diagnosing RAG/agent failures via structured tracing and fixing retrieval-quality issues (freshness checks, filters, schema enforcement). Also supports pre-sales by leading developer demos/workshops and building targeted POCs to address scalability/reliability objections and drive adoption.

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