Vetted Problem Solving Professionals

Pre-screened and vetted.

DC

Senior Business Analyst specializing in data analytics and business intelligence

Dallas, TX8y exp
Goldman SachsSaint Louis University
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AD

Senior AI/Machine Learning Engineer specializing in RAG and MLOps

Odessa, TX8y exp
DataRobotJohns Hopkins University
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BC

Mid-level DevOps Engineer specializing in cloud-native CI/CD and Kubernetes

Arlington, VA5y exp
CoforgeWilmington University
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VA

Senior Data Engineer specializing in cloud-scale pipelines and legal data utilities

Austin, TX6y exp
IBMUniversity of North Texas
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VD

Vismay Devjee

Screened ReferencesModerate rec.

Mid-level GenAI Engineer specializing in AI agents, RAG, and LLM evaluation

Boston, MA2y exp
Fidelity InvestmentsNortheastern University

Asset Management Risk professional at Fidelity Investments who built and productionized an agentic RAG platform enabling compliance and analysts to query 10,000+ fund documents with cited answers in seconds. Implemented structure-aware semantic chunking (AWS Textract), hierarchical retrieval, and hybrid search to raise accuracy from 68% to 94%, and built an evaluation framework tracking accuracy/latency/cost/hallucinations—delivering 40+ hours/month saved and zero critical production failures.

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KS

Karan Shah

Screened

Mid-level Software & Robotics Engineer specializing in autonomous systems and ROS 2

USA3y exp
Boston DynamicsUniversity of Texas at Arlington

Robotics software engineer focused on production-grade autonomy in GPS-denied environments, building full navigation stacks (perception, EKF/UKF sensor fusion, planning, control) in ROS2. Integrated YOLOv8/semantic segmentation/RL policies into real-time NAV2 pipelines via a custom perception-aware costmap layer, with emphasis on deterministic control loops, embedded GPU performance, and robust system observability/fault tolerance.

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LL

Liz London

Screened

Senior Program Manager specializing in SAP CRM implementations and process transformation

Israel9y exp
Malam TeamTechnion – Israel Institute of Technology

Post-sales SAP CRM implementation professional with experience at IBM and Malam Team, owning full lifecycle delivery from requirements and process design through configuration, testing, and end-user training. Notably built an SAP UI5 service center dashboard that cut SLA-miss tickets from 20% to 5% and regularly drove cross-functional alignment to unblock complex technical issues.

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Akanksha Agrawal - Mid-Level Full-Stack Software Engineer specializing in event-driven data platforms in Bangalore, India

Mid-Level Full-Stack Software Engineer specializing in event-driven data platforms

Bangalore, India5y exp
SAPUniversity of Illinois Urbana-Champaign

Backend engineer with SAP experience modernizing a legacy Flask/PostgreSQL product master data platform into a modular, stateless, containerized service with Kafka-based background processing and improved observability. Also has hands-on academic/side-project experience operationalizing ML (NLP retrieval with TF-IDF/BERT via FastAPI and CV lane-edge detection inference APIs using PyTorch).

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Dony Permedi - Animation Director specializing in character performance and real-time previs

Dony Permedi

Screened

Animation Director specializing in character performance and real-time previs

20y exp
NickelodeonSchool of Visual Arts

Gameplay/cinematic animator and animation supervisor with 20+ years in CG across games, film/TV, VR/AR, commercials, and apps, including primary animation ownership on Louis Vuitton’s "Louis the Game" (Maya-to-Unreal). Strong real-time pipeline and mocap cleanup/export expertise (FBX), known for diagnosing issues like gimbal lock and coordinating with rigging/pipeline/Unreal teams; recently supervised an unreleased 8-minute Unreal-rendered cinematic trailer.

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PR

Senior HRIS and Compensation Analyst specializing in benefits administration

Minneapolis, MN5y exp
TargetUniversity of the Cumberlands

Compensation and payroll professional with hands-on experience supporting end-to-end U.S. payroll and compensation cycles in Workday. Stands out for building Excel-based validation and reconciliation models, resolving HRIS/payroll/finance mismatches at the root-cause level, and adding controls that improve payroll accuracy and compensation decision-making.

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SP

Sneha Patil

Screened

Mid-level Financial Analyst specializing in FP&A, forecasting, and regulatory reporting

New York, NY5y exp
JPMorgan ChaseUniversity of Texas at Arlington

Backend-focused software engineer (4+ years) across e-commerce, banking, and healthcare who owned mission-critical checkout/order management end-to-end and improved peak-traffic success rates via resiliency patterns (timeouts/retries/caching) and data-driven iteration. Also built and shipped real-time operational dashboards (React/TypeScript + Spring Boot) using WebSockets and event-stream integrations, with strong experience in Kafka/RabbitMQ-style messaging at scale.

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RK

Rohit Kumar

Screened

Mid-level Data Engineer specializing in large-scale analytics platforms

San Jose, CA5y exp
NutanixUSC

Data/Backend engineer with experience at Naukri building large-scale analytics products over a 130M+ user base, including Spark/Airflow pipelines and Kafka-based clickstream validation with Confluent Schema Registry. Also built an audience segmentation backend (Athena/S3 + Spring Boot APIs) for non-technical internal teams and recently shipped a GenAI customer data audit system (FastAPI/Postgres/Llama) that cut sales-planning validation from ~3 months to ~1 week.

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Sai Dinesh Pusapati - Senior AI/ML Engineer specializing in GenAI agents and LLM workflows in San Francisco, CA

Senior AI/ML Engineer specializing in GenAI agents and LLM workflows

San Francisco, CA6y exp
Scale AIBelhaven University

LLM/AI engineer with production experience building a retrieval-based document intelligence system that extracts information from PDFs/emails, backed by Python + Spark pipelines. Focused on reliability and cost/latency optimization (caching, batch processing) and has hands-on orchestration experience with Airflow (sensors, retries, alerts). Also partnered with business stakeholders to deliver customer feedback classification/summarization for faster sentiment insights.

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Angie Fathalla - Mid-level Technical Consultant specializing in cloud infrastructure and enterprise automation in Clinton, NJ

Mid-level Technical Consultant specializing in cloud infrastructure and enterprise automation

Clinton, NJ7y exp
IBMNYU

AI/LLM engineer focused on production-grade agent systems in high-stakes workflows, including a tax modernization initiative that automated tax form generation for 50,000 users. Demonstrates strong depth in reliability engineering, evaluation loops, and safe orchestration, with quantified improvements including pass-through gains from 62% to 94%, 30% lower token cost, and accuracy improvement from 88% to 99%.

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BB

Biplob Bidari

Screened

Senior Data Engineer specializing in FinTech analytics and ML data platforms

USA5y exp
Goldman SachsUniversity of the Cumberlands

ML/AI engineer with Goldman Sachs experience building production fraud detection and RAG-based trading insights systems end-to-end. Stands out for combining real-time ML infrastructure, GenAI retrieval systems, and compliance-aware design, with measurable impact including nearly 25% false-positive reduction and improved analyst productivity.

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Sai Karthik Chittamuru - Senior Salesforce Developer specializing in AI systems and enterprise cloud solutions in Pittsburgh, PA

Senior Salesforce Developer specializing in AI systems and enterprise cloud solutions

Pittsburgh, PA15y exp
CRMIT SolutionsCarnegie Mellon University

Salesforce-focused engineer with hands-on experience building Sales Cloud and Service Cloud solutions, including a Zoho billing integration for quote/contract workflows and a multi-panel LWC case management dashboard. Stands out for making practical architecture decisions around middleware vs. custom REST, handling idempotency with upsert patterns, and modernizing legacy Aura patterns with Lightning Message Service.

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JA

Jeevan aher

Screened

Junior AI Engineer specializing in fraud detection, credit risk, and LLMs in FinTech

Remote, USA3y exp
JPMorgan ChaseUniversity of Illinois Urbana-Champaign

AI engineer with production experience building a high-accuracy (98%) fraud detection system operating at real-time latency (1–2s) over millions of transactions, using a multi-model pipeline approach to meet performance constraints. Also implemented Airflow-orchestrated workflows (DAGs, retries, alerts) to replace brittle cron scripts and is currently pursuing a master’s project on real-time ASL-to-text conversion.

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WM

Will McEntee

Screened

Mid-level Operations & Analytics Professional specializing in logistics and sports data

Anaheim, CA4y exp
AmazonGeorgetown University

Lifelong basketball player with extensive exposure to elite Southern California high school basketball (Servite/Trinity League) and familiarity with college recruiting through close connections, who applies a structured PFF-style evaluation lens to scouting. Comfortable identifying talent via film and in-person viewing and proactively engaging prospects through social media outreach; also brings experience working demanding overnight/on-call schedules from Amazon last-mile logistics.

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Akhil Jaggari - Mid-level Full-Stack Software Engineer specializing in scalable web platforms and cloud microservices in CA, CA

Akhil Jaggari

Screened

Mid-level Full-Stack Software Engineer specializing in scalable web platforms and cloud microservices

CA, CA6y exp
UberUniversity of North Texas

Backend engineer with fintech/real-estate lending domain experience (Berkadia) building Python/Flask services for indicative loan pricing across Fannie/Freddie workflows. Strong in scalable AWS architectures (S3, Lambda, SageMaker), database performance (PostgreSQL read replicas, indexing, pooling), and high-throughput optimizations (streaming exports, Redis caching) with measurable production impact.

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Vedant Kharwal - Intern AI/ML Engineer specializing in Generative AI and applied machine learning in Mumbai, India

Intern AI/ML Engineer specializing in Generative AI and applied machine learning

Mumbai, India1y exp
LTIMindtreeBoston University

New graduate with hands-on LLM work building a RAG pipeline (HNSW, lexical reranking/boosting, ReAct) and optimizing it through ablation to dramatically reduce latency. Also building a modular personal assistant with a custom wake word model, router-driven agent selection, and integrations like Spotify with secrets managed via .env.

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Arun Gampala - Mid-level Full-Stack Developer specializing in MERN and AWS microservices in TX, USA

Arun Gampala

Screened

Mid-level Full-Stack Developer specializing in MERN and AWS microservices

TX, USA4y exp
MetLifeSouthern Arkansas University

Backend engineer with experience at MetLife and Amazon focused on security and control for internal and customer-facing services. Emphasizes contract-first Python/FastAPI APIs with strong auth (JWT + RBAC/claims), data-layer isolation (RLS/tenant scoping), and reliability practices like incremental refactors, rollback planning, and idempotency to handle retry-driven failure modes.

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FM

Mid-level Cloud Solutions Architect specializing in AWS, DevOps, and agentic AI

Austin, TX4y exp
AmazonUC Riverside

Solutions Architect with hands-on experience driving AWS Partner Network engagements end-to-end (technical reviews, discovery, demos, incentives, marketplace/GTM) to enable revenue outcomes, even when not the direct closer. Known for navigating complex policy/compliance changes with high-revenue partners and for being a go-to Amazon Connect specialist in ambiguous customer environments; also collaborated with founders of a small health tech company on an AI agent concept tied to healthcare workflows and medical records.

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JC

Executive engineering leader specializing in mobile, cloud, and FinTech platforms

Copenhagen, Denmark24y exp
Capital OneUniversity of Florida

Principal engineer with experience across multiple startups, including direct exposure to VC due diligence and early-stage company strategy. Stands out for making pragmatic product decisions—such as steering a startup away from capital-intensive custom hardware toward mobile applications to validate the business faster and focus on the most valuable software layer.

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