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• Location: Remote, USA • Engagement Type: Contract • Federal Security Clearance will be a big plus Position Overview We are seeking an experienced Oracle E-Business Suite (EBS) Subject Matter Expert (SME) to provide functional and technical guidance for an Oracle EBS modernization and migration initiative. The SME will work closely with business stakeholders, project teams, architects, developers, and DBAs to ensure successful planning, design, testing, and implementation activities. Key Responsibilities • Serve as the primary Oracle EBS Subject Matter Expert for business and technical teams. • Analyze current-state Oracle EBS environments and provide recommendations for optimization and modernization. • Support requirements gathering, solution design, and business process analysis activities. • Provide guidance on Oracle EBS modules, integrations, workflows, and best practices. • Review system configurations, customizations, interfaces, and reporting requirements. • Support project planning, testing, validation, and migration activities. • Assist with issue resolution, risk identification, and mitigation planning. • Collaborate with stakeholders to ensure business requirements are met. • Develop documentation, process flows, training materials, and knowledge transfer deliverables. Required Skills & Experience • 8+ years of Oracle E-Business Suite (EBS) experience. • Strong functional and/or technical expertise in Oracle EBS modules. • Experience supporting Oracle EBS implementation, upgrade, migration, or modernization projects. • Knowledge of Oracle EBS architecture, integrations, workflows, and reporting solutions. • Experience working with business stakeholders and technical teams. • Strong analytical, problem-solving, and communication skills. • Experience supporting testing, validation, and business process improvement initiatives. Preferred Qualifications • Oracle EBS certifications are preferred. • Experience with Oracle Cloud applications and cloud migration initiatives. • Experience supporting federal, government, or highly regulated environments. • Project leadership or consulting experience is a plus. • Support project activities during Planning, Iteration 1, Iteration 2, Iteration 3, and User Acceptance Testing (UAT) phases.

Position Overview: We are looking an experienced PeopleSoft Database Administrator with strong Microsoft SQL Server experience to support enterprise PeopleSoft environments. This is an immediate Contract-to-Hire opportunity. Key Responsibilities: Administer PeopleSoft Environments (DEV/TEST/UAT/PROD). * Manage PeopleTools, Application Server, Process Scheduler, Web Server and Integration Broker. * Install, patch, upgrade and clone PeopleSoft and SQL Server environments. * Perform SQL Server backup, recovery, performance tuning and maintenance. * Support production incidents, troubleshooting and root cause analysis. * Work with development, infrastructure and functional teams. Required Skills: * 5+ years of PeopleSoft Administration. * Strong Microsoft SQL Server DBA experience. * People Tools, PUM, Change Assistant and Data Mover * SQL Server performance tuning and HA/DR. * Excellent troubleshooting and communication skills.

Looks like they have a legacy WMS/DC application written in Golang which is managed by some engineer in Poland who travels to Las Vegas whenever they need support. Alo wants to remove this dependency and have a technical engineer who can pick up this application and provide support in Vegas to the operations team

5. CMS/Bynder professional to support digital content management, asset management, and content publishing initiatives. The ideal candidate should have hands-on experience with Bynder DAM, CMS platforms, content workflows, metadata management and integrations with eCommerce or marketing platforms. Key Skills: Bynder Digital Asset Management (DAM) CMS Platforms (Contentful, Adobe Experience Manager, Sitecore, or similar) Content Publishing & Workflow Management Metadata, Taxonomy, and Asset Organization API Integrations and Automation Digital Content Operations eCommerce and Marketing Platform Integrations Strong stakeholder communication and collaboration skills Experience in retail, fashion, or eCommerce environments is highly preferred.

• Location: Remote, USA • Engagement Type: Contract • Federal Security Clearance will be a big plus Position Overview We are seeking an experienced Database Administrator (DBA) with strong Oracle Exadata Cloud Service (ExaCS) expertise to support cloud migration, database modernization, performance optimization, disaster recovery, and production support activities. The consultant will be responsible for administering Oracle databases running on Exadata Cloud Service and supporting the full project lifecycle. Key Responsibilities • Administer and support Oracle databases hosted on Exadata Cloud Service (ExaCS). • Perform Oracle database installation, configuration, patching, upgrades, backup, and recovery activities. • Support database migration projects, including on-premises to OCI migration initiatives. • Monitor database performance and implement tuning and optimization strategies. • Manage Oracle RAC, ASM, Data Guard, RMAN, and high-availability solutions. • Support disaster recovery planning, testing, and business continuity activities. • Execute database refreshes, cloning, and environment management tasks. • Collaborate with infrastructure, application, cloud, and network teams during project execution. • Troubleshoot and resolve database-related issues while maintaining service availability. • Develop operational documentation, migration plans, and support procedures. Required Skills & Experience • 10+ years of Oracle DBA experience supporting enterprise environments. • Strong hands-on experience with Oracle Exadata Cloud Service (ExaCS). • Experience with Oracle Database 12c, 19c, or later versions. • Strong knowledge of Oracle RAC, ASM, Data Guard, RMAN, and performance tuning. • Experience with Oracle Cloud Infrastructure (OCI) and cloud migration projects. • Knowledge of backup, recovery, disaster recovery, and high-availability architectures. • Strong troubleshooting and problem-solving skills. • Excellent communication and documentation skills Preferred Qualifications • Oracle Certified Professional (OCP) certification. • OCI certification is highly preferred. • Experience supporting Exadata migrations and modernization initiatives. • Federal project experience and security clearance are a plus. • Support the full project lifecycle, including Planning, Iteration 1, Iteration 2, Iteration 3, User Acceptance Testing (UAT), Dry Runs, Disaster Recovery (DR) Build & Testing, Production Cutover, and Hypercare activities.

Prime Vendor End Client : Wells Fargo 3 Positions Exp required : 10 Yrs H1B Only F2F Interview The client recently shared additional feedback on where their ideal candidate lands and the skills they'd like us to prioritize during our search. To help ensure we're aligned, please keep the following in mind as you source and screen candidates: Top priority: Experience taking GenAI/LLM solutions from proof of concept into production. Hands-on experience with modern agent development frameworks, particularly Google ADK, as well as LangGraph, CrewAI, AutoGen, Semantic Kernel, or similar. Focus on AI application engineers building enterprise GenAI solutions rather than AI researchers, ML engineers, or data scientists. Machine learning model development is not required. Data science experience is not required. Continue prioritizing candidates with experience in Python, FastAPI, RAG/GraphRAG, Docker, cloud platforms (AWS/Azure/GCP), and LLMOps/LLM evaluation.

Prime Vendor End Client : Wells Fargo 3 Positions Exp required : 10 Yrs H1B Only F2F Interview The client recently shared additional feedback on where their ideal candidate lands and the skills they'd like us to prioritize during our search. To help ensure we're aligned, please keep the following in mind as you source and screen candidates: Top priority: Experience taking GenAI/LLM solutions from proof of concept into production. Hands-on experience with modern agent development frameworks, particularly Google ADK, as well as LangGraph, CrewAI, AutoGen, Semantic Kernel, or similar. Focus on AI application engineers building enterprise GenAI solutions rather than AI researchers, ML engineers, or data scientists. Machine learning model development is not required. Data science experience is not required. Continue prioritizing candidates with experience in Python, FastAPI, RAG/GraphRAG, Docker, cloud platforms (AWS/Azure/GCP), and LLMOps/LLM evaluation.

IP: Capco End Client : Freddie Mac "Skills Needed: +8 years in IBM DataStage development and engineering, building ETL workflows, strong expertise in SQL, UNIX/Linux, Shell Scripting for automation and operation support, metadata and XML logic, translate ETL in to data platforms such as Snowflake, AWS, or Collibra, AI assisted development, automation tools, etc What We're Looking For 6+ years of hands-on experience with IBM DataStage development. Proven experience building end-to-end ETL workflows, including extraction, transformation, and load processes. Strong expertise in SQL, including complex joins, subqueries, window functions, and performance tuning. Solid knowledge of UNIX/Linux fundamentals, including file systems, permissions, and process management. Hands-on experience with shell scripting (bash/ksh) for job automation and operational support. Experience working with DataStage job metadata and XML transition logic. Ability to analyze and translate legacy ETL logic into modern data platforms such as Snowflake, AWS-native services, or data governance tools like Collibra. Familiarity with AI-assisted development or automation tools used to understand, parse, or accelerate ETL modernization efforts. Strong understanding of data warehousing concepts, ETL best practices, and data quality frameworks. Excellent analytical, problem-solving, and communication skills. Bonus Points For Experience with Collibra or other enterprise metadata and data governance platforms. Familiarity with AI-assisted development tools that support code analysis, metadata interpretation, or ETL modernization. Experience supporting enterprise cloud migration or large-scale modernization programs. Knowledge of CI/CD pipelines and DevOps practices for data engineering. Experience working within financial services or other highly regulated industries."

Should an experienced as a .NET Web Developer developing ASP.NET Core MVC applications verifiable ASP.NET experience developing with the C–Sharp (C#) language experience with SQL Server Database Design and development including optimization of queries, creating tables, views, stored procedures, and functions experience developing applications using Entity Framework (EF) 4.0 or later. experience or a demonstrable understanding of N-tier environments as it relates to development and deployment verifiable Service Oriented Architecture (SOA) experience developing and securing Windows Communication Foundation (WCF) experience or a demonstrable understanding of code repository strategies, code promotion strategies and recovery using Team Foundation Server (TFS) Experience developing reports in SQL Server Reporting Services (SSRS) and making them accessible within an MVC web application. experience developing with Visual Studio; 2 years with Visual Studio 2019 experience implementing Asynchronous JavaScript and XML (AJAX) enabled controls within Active Server Pages (ASP).NET Web applications experience or a demonstrable understanding of developing applications that are mobile compliant experience developing a project within the AGILE methodology using TFS / Devops. Experience in Test Driven Development (TDD) or a verifiable experience implementing a testing strategy for applications developed. Experience with microservices

Client is looking for good WMS BA to provide operations support to his team in Memphis and Maryland DC. The resource should have a good understanding of the WMS and SQL to provide support to non-technical folks at these DC’s

We are seeking senior hands-on full stack engineers who have designed, built, and operated GenAI systems in production, and understand failure modes, evaluation, and governance as first-class AI-powered systems. What You'll Do Design and evolve reusable GenAI workflows used across Lending business lines. Develop an enterprise grade AI-based document ingestion and data extraction capability, including traceability, confidence scoring, and human-in-the-loop review. Build AI-powered assistants embedded in Lending systems using agentic workflows. Deliver automated content and deck generation workflows for reporting and approvals. Provide expert advice on GenAI architecture including model selection, orchestration patterns, and evaluation strategy. Establish LLMOps practices: extraction accuracy, assistant reliability, prompts management, and audit monitoring. Design and implement controls for entitlements, PII handling within open-source models in a regulated environment. In the role you are expected to act as a hands-on technical expert, and it has a clear path to becoming a platform owner responsible for shared GenAI standards across Lending. What You'll Bring 2+, dedicated experience in practical application of GenAI solutions in an enterprise business environment. Designing and operating GenAI orchestration frameworks in production beyond vendor examples (e.g., LangChain systems). 5+ years of strong front-to-back engineering experience, focusing on AI/ML platforms and workflows (Python or Java). Proven experience building and operating production-grade GenAI / LLM platforms, applying patterns such as RAG, tool/function calling, agentic workflows, and validated structured outputs. Strong LLMOps expertise, including evaluation harnesses, prompt and version management, regression testing, observability, and reliability measurement in production systems. Hands-on experience building AI-first data ingestion pipelines with measurable quality, accuracy, and reliability. Advanced retrieval experience: advanced vector search, including multi-vector and late-interaction approaches (e.g., ColBERT, chunking), multi-stage retrieval pipelines, metadata filtering, re-ranking. Solid understanding of evaluation metrics and how they shape practical RAG system design (e.g., recall vs precision, latency vs quality, MRR, NDCG). Experience operating GenAI systems through real production failures (model regressions, retrieval degradation, prompt drift, data quality issues) and designing mitigation strategies. Nice to Have Fixed Income or Institutional Lending domain experience. Experience working in regulated environments with strong audit and control requirements. Familiarity with enterprise security, data governance, and entitlement models. Experience designing reusable internal platforms or shared developer tooling. Frontend experience is beneficial (Angular or React).

We are seeking senior hands-on full stack engineers who have designed, built, and operated GenAI systems in production, and understand failure modes, evaluation, and governance as first-class AI-powered systems. What You'll Do Design and evolve reusable GenAI workflows used across Lending business lines. Develop an enterprise grade AI-based document ingestion and data extraction capability, including traceability, confidence scoring, and human-in-the-loop review. Build AI-powered assistants embedded in Lending systems using agentic workflows. Deliver automated content and deck generation workflows for reporting and approvals. Provide expert advice on GenAI architecture including model selection, orchestration patterns, and evaluation strategy. Establish LLMOps practices: extraction accuracy, assistant reliability, prompts management, and audit monitoring. Design and implement controls for entitlements, PII handling within open-source models in a regulated environment. In the role you are expected to act as a hands-on technical expert, and it has a clear path to becoming a platform owner responsible for shared GenAI standards across Lending. What You'll Bring 2+, dedicated experience in practical application of GenAI solutions in an enterprise business environment. Designing and operating GenAI orchestration frameworks in production beyond vendor examples (e.g., LangChain systems). 5+ years of strong front-to-back engineering experience, focusing on AI/ML platforms and workflows (Python or Java). Proven experience building and operating production-grade GenAI / LLM platforms, applying patterns such as RAG, tool/function calling, agentic workflows, and validated structured outputs. Strong LLMOps expertise, including evaluation harnesses, prompt and version management, regression testing, observability, and reliability measurement in production systems. Hands-on experience building AI-first data ingestion pipelines with measurable quality, accuracy, and reliability. Advanced retrieval experience: advanced vector search, including multi-vector and late-interaction approaches (e.g., ColBERT, chunking), multi-stage retrieval pipelines, metadata filtering, re-ranking. Solid understanding of evaluation metrics and how they shape practical RAG system design (e.g., recall vs precision, latency vs quality, MRR, NDCG). Experience operating GenAI systems through real production failures (model regressions, retrieval degradation, prompt drift, data quality issues) and designing mitigation strategies. Nice to Have Fixed Income or Institutional Lending domain experience. Experience working in regulated environments with strong audit and control requirements. Familiarity with enterprise security, data governance, and entitlement models. Experience designing reusable internal platforms or shared developer tooling. Frontend experience is beneficial (Angular or React).

End Client: Citibank 1. Databricks Platform Architecture (Highest Priority) • Designing, configuring, deploying, and securing Databricks on AWS • Classic and serverless workspaces • Platform security, workspace setup, cluster policies, identity/SSO, secret scopes, etc. 2. Terraform / DevOps • Strong Terraform experience • Infrastructure as Code (laC) • Infrastructure provisioning and deployment automation 3. AWS Infrastructure (Nice to Have) • IAM, VPC, Privatel_ink, networking, routing, etc. • The client is looking for someone with working knowledge here, but they are not expecting an AWS networking specialist.

Client: Finara Qualifications: • Bachelor's degree in Computer Science, Software Engineering, MIS or equivalent combination of education and experience • 8+ years of experience as Data Engineer on AWS Stack with experience on DevOps tool • AWS Solutions Architect or AWS Developer Certification required • Solid experience of AWS services such as CloudFormation, S3, Athena, Glue, Glue DataBrew, EMR/Spark, RDS, Redshift, DataSync, DMS, DynamoDB, Lambda, Step Functions, IAM, KMS, SM, EventBridge, EC2, SQS, SNS, LakeFormation, CloudWatch, Cloud Trail • Implement high velocity streaming solutions and orchestration using Amazon Kinesis, AWS Managed Airflow and AWS Managed Kafka (preferred) • Solid experience building solutions on AWS data lake/data warehouse • Analyze, design, development, and implementation of data ingestion pipeline in AWS • Knowledge implementing ETL/ELT for data solutions • End-to-end data solutions (ingest, storage, integration, processing, access) on AWS • Knowledge implementing RBAC strategy/solutions using AWS IAM and Redshift RBAC model • Build & implement CI/CD pipelines for EDP Platform using CloudFormation and Jenkins • Programming experience with Python, Shell scripting and SQL • Knowledge of analyzing data using SQL Stored procedures • Build automated data pipelines to ingest data from relational database systems, file systems, NAS shares to AWS relational databases such as Amazon RDS, Aurora, and Redshift • Build Automated data pipelines to ingest data from Rest APIs to AWS data lake (S3) and relational databases such as Amazon RDS, Aurora, and Redshift. • Good Experience of DevOps practice • Experience with modern source code management and software repository systems (Bitbucket) • Experience with programming languages (Python) • Experience with scripting languages (Shell, Groovy) • Experience with API deployment for tooling integration • Experience using Jenkins, CloudBees (Pipeline as Code, Shared Libraries) • The ability to document exceptions/issues/action plans/meeting minutes/lessons learned accurately and in a timely fashion • Experience with administering DevOps tools in SaaS • Experience using DevOps Tools (SonarQube, Artifactory etc.) • Experience using build tools (Maven, MS Build and Gradle) • Experience using containers (Docker) • Experience using Atlassian suite (Jira, Confluence) • Experience of Infrastructure as Code using CloudFormation • Creating Jenkins CI pipelines to integrate Sonar/Security scans and test automation scripts • Part of DevOps QA and AWS team focusing on building CI/CD pipeline • Responsible for writing and maintaining Jenkins Pipelines Responsibilities: • Designing, building, and maintaining efficient, reusable, and reliable code • Ensure the best possible performance and quality of high scale data applications and services • Participate in system design discussions • Independently perform hands on development and unit testing of the applications • Collaborate with the development team and build individual components into enterprise data platform • Work in a team environment with product, QE/QA, and cross functional teams to deliver a project throughout the whole software development cycle. • Responsible to identify and resolve any performance issues • Keep up to date with new technology development and implementation • Participate in code review to make sure standards and best practices are met • Project management: Agile developers take responsibility for estimating, planning, and managing all tasks and report on progress • Software quality: The Agile developer is also responsible for the quality of the software he/she produces. The team takes responsibility for the quality of the work they produce instead of turning over some code to a separate and independent group for testing • Teamwork: This includes collaboration with all other team members with the aim to take shared responsibility for the overall efforts • Understanding user needs: This is about interacting with users as necessary to clarify requirements

Client: FINRAA Job Description: The DevOps/Infrastructure Engineer builds and maintains cloud infrastructure and deployment pipelines for a generative AI platform. This role is responsible for environment provisioning, container orchestration, CI/CD automation, and infrastructure scaling to support a microservice-based architecture. The DevOps/Infrastructure Engineer takes a broad perspective to infrastructure problems and exercises independent judgment in selecting techniques and evaluation criteria to obtain results. Key Responsibilities: · Provision and manage AWS cloud environments across development, staging, and production tiers · Deploy and operate containerized services and tool servers within a microservice architecture · Manage container orchestration with blue-green and canary deployment strategies · Support infrastructure for platform dependencies including search engines, caching layers, and relational databases · Exercise independent judgment in evaluating and selecting infrastructure approaches and tooling · Build and manage infrastructure on AWS, leveraging services such as ECS, ECR, IAM, VPC, S3, and CloudWatch DevOps & CI/CD · Maintain and extend CI/CD pipelines using shared library patterns for service builds, testing, and deployment across a microservice fleet · Collaborate with developers on container optimization, startup configuration, and environment management · Identify gaps between system components and designs and deliver solutions that enable team autonomy · Develop actionable insights from analyzing infrastructure trends and DevOps best practices, communicating recommendations to management Monitoring, Scaling & Reliability · Implement infrastructure monitoring, alerting, and scaling strategies for AI workloads and supporting services · Ensure platform reliability through capacity planning, performance testing, and incident response processes · Optimize resource utilization and cost across the cloud environment Quality & Testing · Implement and maintain automated infrastructure testing including smoke tests, health checks, and deployment verification · Design and execute load testing and performance benchmarking for platform services and AI workloads · Ensure CI/CD pipelines enforce quality gates including linting, security scanning, and test execution before deployment · Validate infrastructure-as-code changes through automated testing and peer review processes Mentorship & Collaboration · Guide team members in infrastructure best practices, deployment patterns, and operational procedures · Partner within and across teams to meet shared goals and priorities around platform stability and delivery velocity · Champion collaborative resolution of infrastructure issues and contribute to internal process improvement initiatives Security & Compliance · Assist with adherence to technology policies and comply with all security controls · Implement secure coding practices, particularly in handling personally identifiable information (PII) and sensitive regulatory data · Participate in threat modeling and security discussions for API and infrastructure components Understand and apply client's security standards and best practices for regulated financial environments

Client: FINRAA Job Description: The DevOps/Infrastructure Engineer builds and maintains cloud infrastructure and deployment pipelines for a generative AI platform. This role is responsible for environment provisioning, container orchestration, CI/CD automation, and infrastructure scaling to support a microservice-based architecture. The DevOps/Infrastructure Engineer takes a broad perspective to infrastructure problems and exercises independent judgment in selecting techniques and evaluation criteria to obtain results. Key Responsibilities: · Provision and manage AWS cloud environments across development, staging, and production tiers · Deploy and operate containerized services and tool servers within a microservice architecture · Manage container orchestration with blue-green and canary deployment strategies · Support infrastructure for platform dependencies including search engines, caching layers, and relational databases · Exercise independent judgment in evaluating and selecting infrastructure approaches and tooling · Build and manage infrastructure on AWS, leveraging services such as ECS, ECR, IAM, VPC, S3, and CloudWatch DevOps & CI/CD · Maintain and extend CI/CD pipelines using shared library patterns for service builds, testing, and deployment across a microservice fleet · Collaborate with developers on container optimization, startup configuration, and environment management · Identify gaps between system components and designs and deliver solutions that enable team autonomy · Develop actionable insights from analyzing infrastructure trends and DevOps best practices, communicating recommendations to management Monitoring, Scaling & Reliability · Implement infrastructure monitoring, alerting, and scaling strategies for AI workloads and supporting services · Ensure platform reliability through capacity planning, performance testing, and incident response processes · Optimize resource utilization and cost across the cloud environment Quality & Testing · Implement and maintain automated infrastructure testing including smoke tests, health checks, and deployment verification · Design and execute load testing and performance benchmarking for platform services and AI workloads · Ensure CI/CD pipelines enforce quality gates including linting, security scanning, and test execution before deployment · Validate infrastructure-as-code changes through automated testing and peer review processes Mentorship & Collaboration · Guide team members in infrastructure best practices, deployment patterns, and operational procedures · Partner within and across teams to meet shared goals and priorities around platform stability and delivery velocity · Champion collaborative resolution of infrastructure issues and contribute to internal process improvement initiatives Security & Compliance · Assist with adherence to technology policies and comply with all security controls · Implement secure coding practices, particularly in handling personally identifiable information (PII) and sensitive regulatory data · Participate in threat modeling and security discussions for API and infrastructure components Understand and apply client's security standards and best practices for regulated financial environments