Capstone Integrated Solutions

Machine Learning Engineer

• Participate in data discovery workshops to inventory source systems including property management platforms, marketing channels, and CRM data, and translate findings into data lake architecture requirements.
• Design and implement a multi-zone enterprise data lake on Amazon S3 (raw, conformed, enriched, aggregated) with ingest, cleansing, and business layers aligned to the SOW architecture.
• Build batch and streaming data ingestion pipelines using AWS Glue, Amazon Kinesis, and AWS Data Pipeline across CDP, marketing, and property management data sources.
• Implement data transformation and orchestration frameworks using AWS Glue ETL and AWS Step Functions, including AWS Glue Data Catalog for metadata management and discovery.
• Configure Amazon Athena for serverless SQL querying across the data lake; support QuickSight integration with curated data sets for business analytics.
• Develop and deploy ML models on Amazon SageMaker for lead scoring, predictive maintenance, intelligent underwriting risk scoring, and AI-powered audience segmentation.
• Integrate Amazon Bedrock foundation models to enable generative AI capabilities including customer profile enrichment, hyper-personalization, and intelligent marketing automation.
• Use Kiro CLI to accelerate AI-assisted development workflows, spec-driven pipeline implementation, and automated code generation tasks.
• Design and implement entity resolution pipelines using Amazon Entity Resolution to identify, deduplicate, and merge customer records into unified golden records.
• Implement real-time and batch data synchronization pipelines between source systems and the Customer Data Platform (CDP).
• Support Azure data lake migration: conduct discovery, assess schemas and transformation logic, provision AWS target environments, execute migration via AWS DataSync, and perform data validation and reconciliation.
• Implement data lake security using AWS Lake Formation, including row-level security and column-level encryption.
• Build and maintain data models to support Customer 360 views, ML feature stores, and executive analytics dashboards.
• Ensure data quality, validation, and integrity across all pipeline stages and ML model outputs; support UAT for data-dependent features.
• Collaborate with Full Stack, DevOps/MLOps, and AWS engagement teams; contribute to architecture documentation, pipeline runbooks, and data governance documentation.

Senior Data/ML Engineer – AWS

Business Analyst

• Partner with business stakeholders to document, validate, and refine MFP business processes and workflows.
• Lead and facilitate User Acceptance Testing (UAT): write test scripts, coordinate testing sessions, track defects, and drive resolution.
• Develop and deliver end-user training materials including job aids, quick reference guides, and instructor-led training sessions.
• Create and maintain use cases, business requirements documentation, and functional specifications aligned with the MFP implementation.
• Act as a subject-matter resource to end users during go-live and hypercare periods, answering functional questions and escalating issues appropriately.
• Collaborate closely with technical consultants and vendors to translate business needs into system configuration requirements.
• Support change management activities including stakeholder communication, impact assessments, and readiness reviews.
• Facilitate working sessions and workshops with planning, merchandising, and finance teams to gather requirements and validate solution design.
• Assist with data validation and reconciliation to ensure planning outputs align with business expectations.
• Contribute to future-phase demand forecasting implementation as the engagement progresses (Board / Tulio).

Functional Business Analyst

Full-stack Engineer

• Design and develop the application architecture, UI/UX, and technical requirements during the Discovery & Design phase.
• Build and deploy a document upload portal enabling subcontractors to submit insurance certificates, bonding letters, and financial statements.
• Develop RESTful and serverless APIs using AWS Lambda and Amazon API Gateway to support frontend/backend integration.
• Integrate AI-powered document validation and exception management workflows driven by Amazon Bedrock.
• Develop and host frontend applications using AWS Amplify and Amazon S3.
• Participate in CI/CD pipeline setup, automated testing, and deployment to production environments.
• Collaborate with cross-functional team members including AI/ML, DevOps, and Data Engineering resources.
• Conduct integration testing, support user acceptance testing (UAT), and develop user training materials.
• Contribute to knowledge transfer documentation and post-deployment operations guides.

Senior Full Stack Developer

DevOps Engineer

• Collaborate with cross-functional engineering, infrastructure, and AI teams to design, implement, and maintain scalable AWS cloud environments and CI/CD pipelines.
• Build, automate, and manage AWS-based infrastructure supporting development, production, and AI/ML workloads.
• Design and maintain Infrastructure as Code (IaC) solutions using Terraform, AWS CDK, and CloudFormation.
• Develop and optimize CI/CD pipelines using Azure DevOps and GitHub Actions/GitHub CI/CD workflows.
• Support deployment, monitoring, automation, and operational excellence across cloud-native applications and services.
• Work closely with development and AI teams to integrate modern AI tooling and automation capabilities into engineering workflows.
• Implement best practices around reliability, scalability, observability, security, and performance optimization in AWS environments.
• Participate in architecture discussions, infrastructure planning, troubleshooting, and continuous improvement initiatives.
• Support MLOps-related workflows and infrastructure for AI-enabled applications and services.

AWS DevOps, MLOps Engineer

• Collaborate with cross-functional teams to design, implement, and maintain cloud infrastructure and CI/CD pipelines.
• Build, automate, and manage AWS-based environments to support development and production systems.
• Work closely with development teams to deploy, monitor, and optimize applications and services in AWS.
• Support infrastructure as code (IaC) practices and maintain system reliability, scalability, and security.
• Participate in the full lifecycle of infrastructure and deployment processes, from planning and configuration to monitoring and continuous improvement.

AWS DevOps Engineer

Data Engineer

• Lead data architecture design, API assessment, and ETL requirements gathering during the Discovery & Design phase.
• Develop and configure CMIC ERP API integration to establish reliable data exchange between the ERP system and the AWS platform.
• Design and implement data pipelines using AWS Glue for ETL processing of subcontractor documents and ERP data.
• Integrate Amazon Textract to extract structured data from insurance certificates, bonding letters, and financial documents.
• Build and maintain data models to support AI-powered validation, risk profiling, and executive reporting.
• Configure Amazon S3 data lake architecture to store and manage raw, processed, and curated data assets.
• Implement AWS Lambda and AWS Step Functions to orchestrate data workflows and automated processing pipelines.
• Develop and expose data through Amazon API Gateway to support application and dashboard consumption.
• Ensure data quality, validation, and integrity across all integration points and pipeline outputs.
• Conduct data integration testing and support user acceptance testing (UAT) for data-dependent features.
• Collaborate with Full Stack, AI/ML, and DevOps team members to ensure seamless end-to-end data flows.
• Contribute to knowledge transfer documentation, data pipeline runbooks, and operations guides.

Senior Data Engineer – AWS

Scrum Master

• As an AWS Architect & Developer, you will engage with and enable Clients and Partners of Capstone to achieve extensive business value by migrating and modernizing technology landscapes to AWS and helping them accelerate innovation.
• You will collaborate with a multiple party team to design modern target architectures optimized for business agility, innovation, performance, resiliency, cost, and more.
• Create, articulate, and position an innovative and compelling value proposition so that customer executives clearly realize the benefits and transformation value of migrating to AWS.
• Define and execute technical migration and modernization strategies by working with highly technical teams.
• Deliver modern architectures such as micro services and event driven architectures using managed services and cloud native capabilities.
• Engage with development, infrastructure, security and IT operations teams at the customer and identify repeatable patterns and architectures for cloud migration.
• Work closely with Client and Partner teams to streamline their delivery of business solutions on the AWS platform. This includes automation of builds and helping with adopting new cloud services.
• Identify critical and emerging technologies, techniques, tools, data sources, and platforms in the infrastructure engineering field, including cloud-based solutions, that support and extend predictive modelling/machine learning solutions.
• Work as a “Hands-on” team member as needed.

• Design and develop the application architecture, UI/UX, and technical requirements during the Discovery & Design phase.
• Configure and integrate AWS SES for automated email delivery and Amazon QuickSight for executive-facing dashboards.
• Build and deploy a document upload portal enabling subcontractors to submit insurance certificates, bonding letters, and financial statements.
• Develop RESTful and serverless APIs using AWS Lambda and Amazon API Gateway to support frontend/backend integration.
• Create real-time status and risk profiling dashboards in Amazon QuickSight integrated with CMIC ERP data.
• Integrate AI-powered document validation and exception management workflows driven by Amazon Bedrock.
• Build and manage automated subcontractor outreach features including personalized email generation and response tracking via Amazon SES.
• Develop and host frontend applications using AWS Amplify, Amazon S3, and Amazon CloudFront.
• Participate in CI/CD pipeline setup, automated testing, and deployment to production environments.
• Collaborate with cross-functional team members including AI/ML, DevOps, and Data Engineering resources.
• Conduct integration testing, support user acceptance testing (UAT), and develop user training materials.
• Contribute to knowledge transfer documentation and post-deployment operations guides.