Vetted Data Ingestion Professionals

Srikanth Reddy

Screened

Mid-level AI/ML Engineer specializing in GenAI and financial risk & compliance analytics

Plainsboro, NJ7y exp

“Built and deployed a production LLM-powered financial risk and compliance platform to reduce manual trade exception handling and speed up insights from regulatory documents. Implemented a LangChain multi-agent workflow with structured/unstructured data integration (Redshift + vector DB) and emphasized hallucination reduction for regulatory safety using Amazon Bedrock. Strong MLOps/orchestration background across Kubernetes, Airflow, Jenkins, and monitoring/testing with MLflow, Evidently AI, and PyTest.”

Sai Swetha Bodlapati

Screened

Senior Data Engineer specializing in Spark, Kafka, and Databricks Lakehouse platforms

Dallas, TX5y exp

“Data engineer at Fidelity who built and operated a real-time financial transactions lakehouse on AWS/Databricks, processing millions of records daily with Kafka streaming. Demonstrated strong reliability and data quality practices (watermarking, idempotent Delta writes, validation/reconciliation, observability) and delivered measurable improvements (~30% faster jobs and ~30% fewer data issues) while enabling trusted gold-layer analytics for downstream teams.”

Sanskruti Raut

Screened

Mid-level AI/ML & Full-Stack Engineer specializing in LLM agents and medical RAG systems

Remote, USA4y exp

“Full-stack engineer at an early-stage startup building an agentic AI application for enterprise systems, combining customer-facing Next.js/React UI work (30% faster load times) with backend/workflow orchestration using FastAPI + n8n, Redis, and RabbitMQ. Previously at Deloitte USI, built BDD Selenium/Java automation and managed 200+ defects end-to-end using JIRA/JAMA to support on-time production releases.”

Jorge Mendoza

Screened

Senior Full-Stack Developer specializing in Python, AWS serverless, and data workflows

Remote11y exp

“Backend/data engineer from ALDI Tech Hub who modernized legacy analytics (Excel/SAS) into production-grade Python services on AWS serverless (FastAPI on Lambda behind API Gateway with Step Functions). Strong in reliability and operations (Cognito auth, retries/timeouts, structured logging, CloudWatch alarms) and data pipelines (Glue ETL with schema evolution); delivered measurable SQL tuning gains (30s to 2s, 70% CPU reduction).”

Rushwant K

Screened

Mid-Level Full-Stack Software Engineer specializing in FinTech and microservices

United States, Remote4y exp

“Backend engineer with experience at Discover, Dell, and Carpus building high-concurrency microservices and secure APIs. Delivered measurable impact in fintech workflows by integrating credit bureaus (TransUnion/Experian), cutting loan processing from days to minutes and reducing latency 65% through PostgreSQL tuning and caching. Strong in production security patterns (JWT/RBAC, Postgres row-level security for multi-tenant isolation) and low-risk migrations (shadow mode + incremental rollout).”

“Analytics-focused candidate with experience building SQL/Python pipelines and dashboards for donor, campaign, and website performance reporting. They have worked with messy multi-source data, standardized metric definitions, and delivered automated reporting that reportedly reduced manual effort by about 80%.”

“Built end-to-end ML and GenAI systems at Northern Trust, including a production RAG-based document intelligence platform for financial reports and contracts. Stands out for combining strong MLOps execution with practical product judgment—improving forecast accuracy by 22%, document review accuracy by 38%, and cutting deployment time by 45% while keeping latency and reliability production-ready.”

“ML/AI engineer with strong production ownership across predictive ML and Generative AI systems. They’ve delivered measurable business impact through real-time churn/drop-off prediction, RAG-based document QA, and scalable LLM optimization, with a consistent focus on reliability, safety, latency, and developer productivity.”

“Backend engineer who shipped a Spring Boot transactions/points feature while using AI selectively for boilerplate and test ideas, keeping core system design decisions in human hands. Stands out for rigorous validation of AI output against database behavior, concurrency, idempotency, and failure scenarios, and has also built a lightweight planner -> code gen -> validator agent-style pipeline with step-level logging and retries.”

“Full-stack and AI product engineer with strong AWS/Snowflake experience who built an internal feature flag platform and helped migrate a cybersecurity insights product into a multi-agent AI chat interface. They report production scale of 1M+ embeddings and 50k+ monthly queries, with outcomes including an 80% reduction in analyst work and dashboard generation in 7 minutes; the work was also featured by Claude and AWS.”

“Early-career/new-grad candidate who built TrendScout AI, an evidence-first market intelligence agent that ingests messy news, extracts entities/events, builds a Neo4j knowledge graph, and answers questions via RAG with citations. Achieved ~95% retrieval relevance by combining ChromaDB semantic search with graph-based retrieval and validating outputs through human evaluation and guardrails to prevent hallucinations.”

“Electrical/embedded engineer who owned the end-to-end electronics and firmware for an ultra-portable desalination product at Nona Technologies, taking it from research concept through prototype, PCB bring-up, and iterative testing. Brings hands-on experience with harsh-environment hardware, mixed-voltage control systems, safety-critical monitoring, and designing consumer devices to be plug-and-play for non-technical users.”

“ML/AI engineer with healthcare payer experience (Signal Healthcare, Cigna) who has shipped production fraud/claims prediction systems using Python/TensorFlow and exposed them via FastAPI/Flask microservices integrated with EHR and Salesforce. Emphasizes operational reliability and trust—Airflow-orchestrated pipelines with data quality gates plus SHAP-based interpretability, A/B testing, and drift/debug workflows—backed by reported outcomes of 22% lower false payouts and 17% higher model accuracy.”

“Significant contributor/maintainer to an open-source JavaScript event-tracking client SDK, owning API consistency/backward compatibility, high-load batching and retry/backoff improvements, and test/CI + documentation upgrades. Diagnosed production-like issues (missing events under load) via reproduction and logging, then reduced GC pressure and improved predictability with a ring-buffer-based batching redesign while actively triaging issues and reviewing PRs.”

“Backend/ML engineer who built an end-to-end greenwashing detection system for corporate ESG reports: Python preprocessing pipeline, logistic regression + fine-tuned DistilBERT models, and a Dockerized FastAPI inference service optimized for latency. Internship experience maintaining GitLab CI/CD for TypeScript services (Jest/Playwright), improving pipeline stability and test determinism; familiar with Kubernetes/GitOps concepts and AWS CLI/SSO.”

“Infrastructure/operations engineer with hands-on production IBM Power/AIX (AIX 7.x, VIOS, HMC) and PowerHA/HACMP clustering experience, including DLPAR changes, failover testing, and incident recovery. Also delivers modern cloud DevOps work—GitHub Actions CI/CD for Docker-to-Kubernetes on AWS and Terraform-based provisioning of core AWS infrastructure (VPC/EKS/RDS/IAM) with controlled rollouts and drift checks.”

“Full-stack engineer with healthcare and finance experience who has owned end-to-end production systems across Azure and AWS. Built a real-time clinical dashboard at Centene (React + FastAPI + Azure Event Hubs) that cut data latency from ~12 minutes to under 1 minute and was associated with a 30% reduction in intervention delays. Also delivered MVPs in high-ambiguity environments at Accenture during monolith-to-microservices migration, improving uptime and maintainability with measurable results.”

“Data engineer with Charter Communications experience modernizing large-scale AWS data lake pipelines: ingesting S3 data, validating against legacy systems, transforming with PySpark/Spark SQL, and serving via Iceberg/Delta tables. Worked at 50M–300M record scale, delivered >99.5% data match, and built monitoring/alerting (CloudWatch/SNS) plus retry orchestration (Step Functions) and data quality gates (Great Expectations).”

“Backend engineer who built an AI-driven "Smart Feedback Analyzer" API (Flask → FastAPI) that processes user feedback with NLP (Hugging Face + OpenAI) and returns structured insights. Demonstrates strong production-minded architecture: stateless services, Cloud Run + Docker deployment, Redis/Celery background processing, and Postgres/SQLAlchemy performance tuning (EXPLAIN ANALYZE, indexing, N+1 fixes), plus multi-tenant data isolation via JWT/API-key derived tenant IDs.”

Arunkumar Gangula

Screened

Senior Full-Stack Software Engineer specializing in distributed systems and cloud microservices

Tempe, Arizona11y exp

“Product-minded full-stack engineer from CouponDunia who owned end-to-end notification and recommendation services at million-user scale. Built internal admin/analytics and operations dashboards in React/TypeScript with typed contracts and scalable Node.js REST APIs, and has deep microservices experience with Kafka/RabbitMQ (idempotency, retries/DLQs, partitioning, consumer tuning, and observability).”

“Accenture data engineer who greenfielded a supply-chain lakehouse platform, building an end-to-end medallion/Delta pipeline ingesting ~1.4TB/day from 17+ ERP/WMS/TMS/shipment sources. Delivered Gold datasets to Redshift/Synapse/Databricks SQL powering Power BI/Tableau with a 99.5% SLA, while cutting runtime 30% and cloud costs 16% through Spark/Delta optimizations and robust data quality controls.”

Surya Ravula

Screened

Junior Software Engineer specializing in backend systems and AI automation

Hyderabad, India2y exp

“Backend/platform engineer with Boston Scientific experience building secure healthcare integrations, resilient AWS data pipelines, and a production internal LLM support chatbot. Stands out for combining legacy-system modernization, strong reliability practices, and measurable operational impact in regulated healthcare environments.”

Sadiya Bhawania

Screened

Senior Software Engineer specializing in AI platforms and full-stack systems

California, USA5y exp

“Full-stack TypeScript engineer with early-stage startup experience (HomePulse; sole US engineer) who ships and owns production features end-to-end—routing/state design, API contracts, caching/pagination, and post-launch monitoring/optimization. Has delivered performance-sensitive React UIs (virtualized large datasets, React Query caching, Suspense loading patterns) and built durable job-queue workflows with idempotency/retries, plus SQL Server relational modeling for internal ticketing and knowledge-retrieval workflows.”

“Full-stack engineer with recent startup-style experience at SynapOne building enterprise B2B SaaS platforms for compliance and operational review workflows. Stands out for turning ambiguous business problems into production systems, including AI-assisted workflow automation, scalable Go/Python microservices, React/TypeScript interfaces, and PostgreSQL/Elasticsearch-backed platforms used daily by customers.”