Vetted AWS Step Functions Professionals

Pre-screened and vetted.

JS

Senior Software Engineer specializing in cloud-native backend systems on AWS

Kingman, Arizona8y exp
FundriseNorthern Arizona University
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DE

Mid-level AI/ML Engineer specializing in MLOps, LLMs, and real-time AI systems

Memphis, TN5y exp
FedExUniversity of Memphis
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MA

Entry-Level Software Engineer specializing in ML, cloud, and cybersecurity

NY, USA0y exp
ConcentrixNorth Carolina State University
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AA

Mid-Level Generative AI Engineer specializing in LLM apps, RAG, and cloud deployment

5y exp
State FarmCleveland State University
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SR

Senior Data Engineer specializing in AWS cloud data platforms and streaming analytics

Westlake, TX8y exp
Charles SchwabUniversity of North Texas
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WL

Senior Machine Learning Engineer specializing in GenAI, LLMs, and MLOps

Houston, TX11y exp
Paramount+University of Houston
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AL

Senior Machine Learning Engineer specializing in GenAI, LLMs, and MLOps

Houston, TX11y exp
Paramount+University of Houston
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RC

Mid-level Software Engineer specializing in FinTech and AI platforms

USA5y exp
Morgan StanleyUniversity at Buffalo
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RK

Mid-level Software Engineer specializing in distributed backend systems for FinTech

Los Angeles, CA5y exp
BlackRockCalifornia State University, Long Beach
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SA

Mid-level Software Engineer specializing in backend systems and AI

Austin, TX3y exp
Evernorth Health ServicesRochester Institute of Technology
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KM

Director-level Engineering Leader specializing in cloud platforms, AI/ML, and scalable SaaS

Brampton, Canada16y exp
Chordline
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SD

Senior Data Scientist specializing in NLP, MLOps, and cloud ML platforms

Westfield Center, OH7y exp
Westfield Insurance
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AR

Mid-level Full-Stack Developer specializing in cloud-native microservices

Oregon, USA5y exp
Salesforce
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AI

Senior DevOps/SRE Engineer specializing in multi-cloud infrastructure and Kubernetes

Chicago, IL11y exp
Northwestern Memorial Hospital
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SN

Senior Data Engineer specializing in cloud data platforms and ML pipelines

Atlanta, GA8y exp
Berkshire HathawayUniversity of Alabama at Birmingham

Data engineer focused on AWS-based enterprise data platforms, owning end-to-end pipelines from multi-source batch/stream ingestion (Glue/Kinesis/StreamSets/Airflow) through PySpark transformations into curated datasets for Redshift/Snowflake. Emphasizes production reliability with strong monitoring/observability and data quality gates, and reports ~30% performance improvement plus improved SLAs and latency after optimization.

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Yogita Adari - Mid-level AI Engineer specializing in generative and multimodal systems in San Francisco, CA

Yogita Adari

Screened

Mid-level AI Engineer specializing in generative and multimodal systems

San Francisco, CA4y exp
Handshake AISyracuse University

Built and productionized an agentic LLM automation system for an insurance client to determine medication eligibility, using prompt-chaining plus a RAG pipeline over policy rules and deploying on AWS (Lambda/Step Functions, Bedrock) with a serverless architecture. Addressed major data/schema mismatch issues via a semantic matching pipeline and validated performance through human agreement scoring, A/B testing, KPI monitoring, and confidence-based human-in-the-loop review.

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Alex Guzman - Principal Software Engineer specializing in cloud infrastructure and identity systems in Denver, CO

Alex Guzman

Screened

Principal Software Engineer specializing in cloud infrastructure and identity systems

Denver, CO17y exp
LTIMindtreeWestwood College

Senior backend-leaning engineer with experience spanning an 8-person early-stage startup and production microservices environments. They helped deliver an MVP for a fintech/charitable donations product by building a resilient abstraction API across multiple rewards vendors, and more recently maintained Go services at scale with Kubernetes autoscaling for workloads reaching roughly 1 million requests per day.

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VW

Senior Python Backend Engineer specializing in scalable APIs and cloud-native microservices

Arlington, TX12y exp
SnapStreamTexas A&M International University

Backend/data platform engineer who has built and operated a cloud-native media ingestion/processing platform in Python (Django/DRF, FastAPI) with Kafka, Postgres, and Redis, emphasizing multi-tenant security and reliability. Delivered AWS production systems combining EKS and Lambda with Terraform + GitHub Actions/Helm, and built Glue-based ETL pipelines with strong schema-evolution and data-quality practices; also modernized SAS analytics into Python on AWS. Seeking fully remote roles with a $120K–$140K base range.

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AG

Senior Backend Engineer specializing in AI/LLM and Healthcare Claims

8y exp
UnitedHealth GroupIndiana University Bloomington

JavaScript/React performance-focused engineer who contributed upstream to an open-source virtualization/pagination library, fixing overlapping-fetch race conditions and introducing prefetch/deduping patterns that cut load times from ~3s to <900ms and reduced render thrash ~35%. Also built healthcare automation systems (clinical summary and claims triage), including a FastAPI + RAG pipeline that retrieved CPT/ICD evidence, improving decision accuracy from 67% to 86% and reducing turnaround time by 40%.

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HT

Mid-level Machine Learning Engineer specializing in LLMs, agentic AI, and risk/fraud modeling

San Francisco, CA3y exp
The Research Foundation for SUNYUniversity at Buffalo

Built and productionized an agentic LLM workflow during a summer internship to transform unstructured clinical reports into analytics-ready structured data, using a LangChain multi-agent design plus an LLM-as-a-judge layer to control quality in a regulated setting. Also has experience orchestrating ML pipelines at Piramal Capital using AWS Step Functions/EventBridge/CloudWatch, with strong emphasis on observability, evaluation rigor, and measurable impact (80–90% reduction in manual data entry).

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AB

Senior Data & Platform Engineer specializing in cloud-native streaming and distributed systems

USA10y exp
JPMorgan ChaseNew York Institute of Technology

Financial data engineer who has built and operated high-volume batch + streaming pipelines (200–300 GB/day; 5–10k events/sec) using AWS, Spark/Delta, Airflow, Kafka, and Snowflake, with strong emphasis on data quality and reliability. Demonstrated measurable impact via 99.9% SLA adherence, major reductions in bad records/nulls, MTTR improvements, and significant latency/runtime/query performance gains; also built a distributed web-scraping system processing 5–10M records/day with anti-bot and schema-drift defenses.

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