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Vetted Dashboarding Professionals

Pre-screened and vetted.

DashboardingPythonAWSCI/CDDockerSQL
VS

Vignesh Shanmugasundaram

Screened

Junior Software Engineer specializing in full-stack development and applied ML

New York, NY2y exp
AmazonNYU

“Full-stack engineer with experience at Zoho and Amazon who has owned production systems end-to-end, including a monolith-to-microservices migration using Kafka and Cassandra that improved search latency ~25% and increased throughput without data loss. Also built a hackathon project (Buildwise) into a sold product for a construction company (AI-driven document compliance checks) and shipped an IoT-based parking availability MVP in 3 weeks.”

PythonCC++JavaJavaScriptSQL+163
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WL

winston lo

Screened

Junior Software Engineer specializing in AI agents, RAG, and full-stack development

Remote2y exp
Tresle AIUC Berkeley

“Backend engineer who built and iterated a secure, multi-tenant RAG system over a large document corpus, emphasizing strict RBAC/ACL isolation, hybrid retrieval (vector+keyword), reranking, and strong observability to balance relevance, latency, and cost. Also led production refactors/migrations using strangler + feature flags/dual writes and has experience catching subtle real-world failure modes (including in a sensor calibration optimization pipeline).”

PythonJavaJavaScriptTypeScriptSQLHTML+114
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DS

Darsh Sharma

Screened

Mid-level Software Engineer specializing in ML systems and microservices

Madison, WI2y exp
TeradataUniversity of Wisconsin–Madison

“Teradata Text Security intern who built a production LLM-powered planner agent that decomposes complex tasks into dependency-aware subtasks (DAG/topological graph) and executes them via a custom orchestrator with parallelism, status tracking, and error handling. Also contributed to an HR-facing internal document chatbot concept to streamline onboarding, showing cross-functional collaboration.”

CC++CUDAPythonJavaSQL+101
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SB

Sowmya Battu

Screened

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

Greater Seattle Area, WA6y exp
AmazonUniversity of Houston

“Amazon experience integrating LLM-powered chat automation into Amazon Connect contact-center workflows, taking prototypes to production with compliance-minded guardrails, schema/policy validation, and robust fallbacks. Regularly supports rollout and adoption via developer workshops, integration guides, and customer calls, with strong production triage and observability practices.”

JavaKotlinPythonTypeScriptJavaScriptSQL+89
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MS

Madhu Sudhan Reddy Konda

Mid-Level Software Engineer specializing in backend, distributed systems, and AI/ML platforms

Atlanta, GA5y exp
Georgia State UniversityGeorgia State University
TypeScriptGoPythonJavaJavaScriptC#+117
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SB

Supriya Besam

Mid-Level Full-Stack Software Engineer specializing in FinTech and data platforms

Jersey City, NJ4y exp
Capital OneUniversity of Cincinnati
PythonSQLJavaScalaHTMLCSS+48
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VA

vinay Acha

Mid-level UI/UX Designer specializing in user research, prototyping, and compliant onboarding flows

Remote, USA5y exp
McKinsey & CompanyPace University
Usability TestingA/B TestingUser Acceptance Testing (UAT)Data VisualizationRegulatory ComplianceStakeholder Management+37
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AV

AshacharanReddy Veega

Mid-level Software Development Engineer specializing in AWS cloud services and distributed systems

Atlanta, GA6y exp
AmazonUniversity of Cincinnati
AWS CloudFormationAPI GatewayAutomationCloud ComputingComplianceEnd-to-End Testing+76
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RM

Rohith M

Mid-level Full-Stack Developer specializing in AWS serverless and Java/Spring

Austin, Texas6y exp
AppleUniversity of Bridgeport
JavaPythonJavaScriptReactAngularBootstrap+79
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SC

Sai Charan Bussa

Senior Software Engineer specializing in cloud-native microservices and real-time data pipelines

CA, USA7y exp
NVIDIAEastern Illinois University
PythonJavaC++C#JavaScriptTypeScript+114
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TS

Tyler Swanson

Senior AI/ML Engineer specializing in production AI systems for healthcare and finance

Austin, TX13y exp
AspirusUniversity of Texas at Austin
PythonScalaSQLJavaC++TensorFlow+72
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AR

Aishwarya Raju Khatwani

Mid-Level Software Engineer specializing in cloud-native distributed systems

Seattle, WA6y exp
Mercedes-BenzRochester Institute of Technology
AgileAlertingAmazon SQSAmazon SNSAWSAWS Lambda+52
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AC

Ashutosh Choudhari

Screened

Mid-level AI/ML Engineer specializing in LLM applications and cloud-native systems

Remote2y exp
PYRAMYDCarnegie Mellon University

“LLM engineer who has shipped production AI systems, including an RFP requirements extraction platform (OpenAI o4-mini + Azure AI Search + FastAPI) achieving 90%+ accuracy and ~5x throughput through grounding, structured outputs, parallelization, and caching. Also partnered with legal/compliance stakeholders at Nexteer Automotive to deliver an AI document comparison tool with traceability and confidence indicators, adopted by non-technical users and saving ~2 FTEs of review time.”

PythonJavaSQLRJavaScriptHTML+116
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CS

Carlee Schiller

Screened

VP Human Resources Business Partner specializing in regulated financial services

Jersey City, NJ10y exp
SMBCTulane University

“HR Business Partner with 8 years supporting a Jersey City office while working closely with distributed teams. Early in career built Excel-based HR analytics dashboards (headcount/turnover/diversity) and ER tracking that became foundational to establishing an HR Data & Analytics function. Experienced partnering with senior leaders and legal on sensitive restructurings/RIFs, including risk analysis, separation planning, and manager coaching.”

Performance ManagementChange ManagementWorkforce PlanningStakeholder ManagementReportingOnboarding+51
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NS

Nagatheja Sharaf

Screened

Mid-Level Software Engineer specializing in cloud-native systems, automation, and LLM-enabled robotics

Sunnyvale, CA6y exp
AmazonIndiana University Bloomington

“React-focused engineer who built a full-stack analytics/test-metrics dashboard (React frontend + Python backend) and turned common UI pieces (data tables, filter panels, chart wrappers) into a reusable internal component library with docs, examples, and basic tests. Strong on profiling-driven performance optimization (React Profiler, memoization) and on owning ambiguous internal-tool projects end-to-end; now planning to package internal patterns into public open-source components.”

PythonPandasNumPySciPyJavaScriptC+126
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RR

Rushi Reddy Lambu

Screened

Mid-level AI/ML Engineer specializing in Generative AI and MLOps

Remote, USA5y exp
McKinsey & CompanyUniversity of North Texas

“GenAI/LLM engineer and architect who built and deployed a production generative AI financial forecasting and scenario analysis platform at McKinsey, leveraging Claude (Anthropic), LangChain, Airflow, MLflow, and AWS SageMaker. Demonstrates strong LLMOps/MLOps rigor (monitoring, drift detection, automated retraining) and deep experience implementing global privacy controls (GDPR, differential privacy, audit trails) while partnering closely with finance executives and legal/IT stakeholders.”

PythonSQLRJavaC++Bash+192
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SK

Sahithi K

Screened

Mid-level Data Engineer specializing in cloud data platforms and streaming pipelines

Boston, MA4y exp
ModernaUniversity of Massachusetts Dartmouth

“Data engineer with experience at Moderna and Block owning high-volume (≈10TB/day) production pipelines on AWS, using Kafka/S3/Glue/dbt/Snowflake with strong data quality and observability practices (schema validation, anomaly detection, CloudWatch monitoring). Also built external financial API ingestion with Airflow retries, throttling/token rotation, and schema versioning, and helped stand up an early-stage biomedical data platform with CI/CD and incident debugging.”

PythonSQLPySparkApache SparkApache KafkaAmazon Kinesis+94
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CS

Chaitanya Sachdeva

Screened

Mid-level Applied AI Engineer specializing in LLM infrastructure and model optimization

San Jose, CA3y exp
AMDUSC

“LLM engineer who has deployed privacy-preserving, real-time workplace risk monitoring over massive enterprise chat/email streams, tackling latency, hallucinations, and extreme class imbalance with model benchmarking, RAG + fine-tuning, and a pre-filter alerting layer. Also built an agentic legal contract drafting system (Jurisagent) using LangGraph/LangChain with deterministic multi-agent control flow, structured outputs, and reliability-focused evaluation/telemetry.”

PythonC++BashLangChainLangGraphNumPy+104
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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.”

ForecastingBudgetingRisk ManagementPredictive AnalyticsData AnalysisData Visualization+81
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AJ

Azra Jiwa

Screened

Senior People Operations Manager specializing in HRIS, compliance, and global mobility

New York, NY7y exp
CharterUpNational University

“People/HR leader focused on scalable org systems—rebuilt performance, leveling, and compensation structures during a growth phase using CultureAmp and Workday data plus manager listening sessions. Known for systems-thinking diagnostics and leader coaching (e.g., delegation/decision-rights mapping freeing 8–10 hours/week), and for using people analytics to reduce attrition via onboarding and manager enablement.”

Performance ManagementChange ManagementWorkforce PlanningProject ManagementJiraConfluence+93
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SK

Sameen Kashfi

Screened

Executive Operations & PMO leader specializing in scaling FinTech, SaaS, and eCommerce organizations

15y exp
Eastern Asset ManagmentGeorge Mason University

“Strategy & operations leader with senior roles at OnDeck, BlockFi, and Protocol Labs who owned founder-level initiatives end-to-end. Notably launched the first crypto credit card, driving 150k first-year sign-ups (vs 30k target) and boosting adoption of other offerings, and later cut time-to-hire from ~6 months to ~6 weeks while rebuilding GTM and operating frameworks.”

Strategic PlanningRegulatory ComplianceGo-to-Market StrategyProgram ManagementProject ManagementCross-Functional Collaboration+119
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