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Vetted Observability Professionals

Pre-screened and vetted.

SL

Senior Software Engineer specializing in backend microservices and data platforms

Colorado Springs, CO12y exp
ZocdocUniversity of Minnesota
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AP

Andres Pegado Boureghida

Screened ReferencesStrong rec.

Engineering executive specializing in cloud-native SaaS for data-intensive, regulated domains

Chicago, IL12y exp
Walker & DunlopIllinois Institute of Technology

Former CTO at Enodo who led development of programmatic parsers to extract unstructured data from real-estate financial documents (rent rolls and T12s), validating with users via prototypes before productionizing. Emphasizes accuracy-driven engineering and scalable test-suite growth based on real user samples, and has experience scoping complex product ideas (e.g., browser-based narrative editor) down to an MVP.

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EK

Edem Kporha

Screened ReferencesStrong rec.

Senior Technical Support/Systems Engineer specializing in secure enterprise operations

Riverside, CA9y exp
Virtuous Automotive GroupValley View University

AppSec-focused engineer with experience supporting federal case management platforms at Armedia (SAST/DAST/SCA, threat modeling, injection remediation) and leading production troubleshooting for Ecobank’s virtual card service across 33 African affiliates. Known for using deep log/SQL/trace analysis to pinpoint TLS and query issues, documenting clear repro evidence, and driving measurable outcomes like eliminating recurring SQL vulnerabilities and stabilizing activation success rates.

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JJ

John Juszczak

Screened

Senior Software Engineer specializing in C++ tooling, CI/CD, and Unreal Engine pipelines

Los Angeles, CA10y exp
Starpunch StudiosDePaul University

Gameplay programmer with hands-on Unreal Engine multiplayer shooter experience, notably overhauling aiming/ADS using Enhanced Input and curve-table-driven response curves plus subtle aim assist. Demonstrates strong networking judgment (client-side prediction vs server authority for anti-cheat) and a systems mindset, adding automation/analytics to speed iteration and improve decision-making.

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NR

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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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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LD

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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SP

Suparshwa Patil

Screened ReferencesStrong rec.

Mid-level Software Engineer specializing in Agentic AI and RAG systems

Remote, California4y 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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MP

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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AM

Arjun Masadi

Screened

Mid-level Full-Stack Developer specializing in cloud-native FinTech and Healthcare platforms

Remote, USA3y exp
Regions BankUniversity of North Carolina at Charlotte

Full-stack engineer (3+ years) who owned an AI-powered customer financial health dashboard end-to-end at Regions Bank, combining React/Java Spring Boot with LangChain + Pinecone for personalized insights. Strong production operations experience on AWS EKS with CI/CD and observability (OpenTelemetry/Prometheus/Grafana), delivering measurable outcomes including 22% support reduction and 99.9% uptime, plus robust third-party financial/clinical integrations.

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AD

Akshay Danthi

Screened

Senior AI Engineer specializing in production GenAI systems

San Francisco, CA8y exp
MajorlyGolden Gate University

AI engineer who has shipped production LLM systems end-to-end, including a natural-language-to-SQL analytics copilot for career advisors that achieved ~95% query success through schema grounding, access controls, and automated regression testing with golden queries. Also builds LangGraph-orchestrated multi-step agents (resume analysis, recommendations) and RAG pipelines (PDF ingestion + FAISS) and partners closely with non-technical users to drive adoption and trust.

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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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FP

Intern Data Scientist specializing in ML, NLP, and MLOps for healthcare and enterprise AI

Madison, WI1y exp
University of Wisconsin–MadisonUniversity of Wisconsin–Madison

Built a production multi-cloud LLM-driven IT ticket automation system using LangGraph, Azure + Pinecone RAG, and an Ollama-hosted LLM on AWS, with Terraform-managed infra and PostgreSQL audit/state tracking for reliability. Also partnered with UW School of Medicine & Public Health students to deliver a glioma survival risk-ranking model, translating clinical feedback into practical pipeline improvements (imputation, site harmonization) and stakeholder-friendly visualizations.

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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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