Patel Vraj Arnav

CTO

Tracy, California, United States9 yrs experience

AI EnabledHighly Stable

Key Highlights

Expert in Generative AI and AWS cloud solutions.
Proven track record in deploying scalable serverless applications.
Strong background in architecture reviews and security compliance.

Stackforce AI infers this person is a SaaS cloud engineer specializing in Generative AI and serverless architectures.

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Skills

Core Skills

Generative AiAwsCloud EngineeringCloud Development

Other Skills

API GatewayAWS BedrockAWS CDKAWS CloudFormationAWS LambdaAWS SageMakerAgile & Waterfall MethodologiesAgile MethodologiesAgile TestingAmazon EC2Amazon Relational Database Service (RDS)AngularJSAnsibleArtificial Intelligence (AI)Azure DevOps Services

About

Experienced Gen AI AWS Engineer with a strong focus on cloud-native architecture, serverless solutions, and Generative AI deployments. Skilled in React front-end UI development and designing, deploying, and managing GenAI chatbot components within AWS using Infrastructure as Code (CDK) in Python and TypeScript. Proficient in configuring and managing Lambda, API Gateway, IAM, S3, DynamoDB, OpenSearch, and RAG pipelines, with hands-on experience in multi-environment deployments (Dev, QA, UAT, Prod) via GitHub Actions CI/CD pipelines. Expert in integrating enterprise tools such as Splunk, SecureWorks, and EntraID (SSO), and setting up CloudWatch → SecureWorks monitoring and alerting for performance and security. Conducts architecture reviews, security gap analysis, and roadmap planning to stabilize, scale, and optimize solutions while ensuring compliance in enterprise cloud environments. Experienced with Amazon Bedrock, foundational LLMs, and RAG pipelines, with expertise in prompt engineering, fine-tuning, and optimizing AI workflows for high-performance, context-aware responses.

Experience

9 yrs

Total Experience

2 yrs 3 mos

Average Tenure

2 yrs 1 mo

Current Experience

Lexisnexis

Generative AI Cloud Engineer

May 2024 – Present · 2 yrs 1 mo

I am leading the design, deployment, and scaling of enterprise-grade Generative AI chatbot platforms within AWS cloud environments, ensuring high availability, security, and compliance. My role involves building multi-environment RAG-based AI solutions powered by Amazon Bedrock and foundational LLMs, integrated seamlessly with legal research workflows. I develop and manage infrastructure using AWS CDK in Python and TypeScript, orchestrating services such as Lambda, API Gateway, IAM, OpenSearch, DynamoDB, and S3 to deliver secure and scalable GenAI-powered applications. I also leverage React for front-end development, GitHub Actions for CI/CD pipelines, and Splunk with CloudWatch/ SecureWorks integrations for monitoring, alerting, and enterprise observability. Additionally, I conduct architecture reviews, security gap analysis, and implement prompt engineering and fine-tuning strategies to optimize LLM performance, enabling LexisNexis to deliver reliable, compliant, and next-generation AI-driven legal research tools.

AWS CDKPythonTypeScriptLambdaAPI GatewayIAM+9

Pax8

AI/ML Engineer – AWS Bedrock & RAG

Aug 2022 – May 2024 · 1 yr 9 mos · Remote

I designed, developed, and deployed enterprise-grade Generative AI solutions leveraging AWS Bedrock and retrieval-augmented generation (RAG) pipelines. I architected cloud-native, serverless applications with a focus on scalability, security, and multi-environment deployment (Dev, QA, UAT, Prod). My work involved integrating React-based front-end UIs with backend AI pipelines, managing Lambda, API Gateway, S3, DynamoDB, and OpenSearch, and provisioning all resources using AWS CDK (Python & TypeScript).
I implemented CI/CD pipelines using GitHub Actions, enabling automated deployments and testing across environments, and integrated CloudWatch with SecureWorks for real-time monitoring and alerting. I also conducted architecture reviews, security gap analysis, and roadmap planning, ensuring stable, secure, and optimized GenAI solutions. Additionally, I fine-tuned foundation LLM models, optimized prompt engineering, and enhanced RAG pipeline performance to deliver accurate, context-aware AI responses for enterprise users.

AWS BedrockRAG pipelinesReactLambdaAPI GatewayS3+6

Dentaquest

Full Stack Cloud Engineer

Apr 2019 – Aug 2022 · 3 yrs 4 mos

I contributed to the design and development of cloud-based solutions for enterprise data management and intelligent automation. I implemented serverless architectures leveraging AWS Lambda, API Gateway, S3, and DynamoDB to handle real-time data processing and secure document workflows. My work included developing React-based front-end dashboards for reporting and workflow management, integrated with backend APIs for seamless user interaction.
I played a key role in infrastructure automation using AWS CloudFormation and CDK, enabling reproducible deployments across multiple environments (Dev, QA, UAT, Prod). I also configured CloudWatch monitoring and alerting, ensuring proactive performance management and system reliability. In addition, I collaborated on architecture reviews, security assessments, and compliance validations, ensuring enterprise standards were met while maintaining scalability and operational efficiency.
Key Contributions:
Developed serverless AWS pipelines to automate document ingestion, processing, and retrieval.
Built React-based dashboards and interfaces for data visualization and enterprise workflow automation.
Implemented IaC solutions with CloudFormation/CDK to enable consistent multi-environment deployments.
Configured CloudWatch alerts and monitoring dashboards to track performance and detect anomalies.
Conducted security and compliance reviews, improving governance and operational resilience.

AWS LambdaAPI GatewayS3DynamoDBReactAWS CloudFormation+4

Accenture

AWS Developer

Jun 2017 – Apr 2019 · 1 yr 10 mos

I worked as an AWS Developer, building cloud-native enterprise solutions that leveraged serverless architecture, scalable search pipelines, and modern front-end technologies. I developed and deployed applications using AWS Lambda, API Gateway, S3, DynamoDB, and Elasticsearch, enabling secure, high-performance data processing and knowledge retrieval systems.
I designed and implemented React-based front-end dashboards and interactive UIs integrated with backend APIs, providing enterprise users with efficient access to internal data and workflows. I automated multi-environment deployments using CloudFormation, ensured operational reliability through CloudWatch monitoring and alerting, and implemented CI/CD pipelines with GitHub and Jenkins to streamline application delivery.
Additionally, I collaborated on architecture reviews, security audits, and compliance checks, designing IAM roles and policies to enforce least-privilege access and maintain enterprise security standards. My work focused on scalability, maintainability, and cost optimization of cloud-native solutions across Dev, QA, UAT, and Prod environments.
Key Contributions:
Built and deployed serverless applications for document processing, search, and knowledge retrieval.
Developed React-based front-end interfaces integrated with secure backend APIs.
Automated multi-environment deployments using AWS CloudFormation templates.
Configured CloudWatch monitoring and alerts for proactive system performance management.
Designed secure IAM roles and policies for enterprise-grade access control.
Implemented CI/CD pipelines with GitHub and Jenkins, improving release efficiency.
Optimized Elasticsearch search pipelines for faster and more relevant data retrieval.
Participated in architecture reviews and compliance audits, ensuring secure and scalable cloud solutions.