Jobs at Cloudelligent

Designs, implements, and supports enterprise Amazon Connect contact center solutions. Configures contact flows, queues, routing, agent workspaces, analytics, recording, and transcription. Develops AWS serverless extensions and integrates Connect with CRM, ERP, ServiceNow, Salesforce, Zendesk, and other platforms. Implements conversational AI using Lex and Bedrock, troubleshoots deployments, leads solution design and workshops, supports customer demonstrations, and contributes to proposals, proof-of-concepts, and go-to-market initiatives.

Manage and improve the full employee lifecycle, including recruitment, onboarding, performance management, training, benefits, engagement, retention, and offboarding. Develop HR policies and frameworks, provide employee and manager support, administer benefits, use HR data for decision-making, and ensure compliance with employment laws. The role also leads employee development initiatives and supports a high-performance culture in a fast-paced technology environment.

Generate and qualify outbound B2B leads for AWS cloud services through cold calls, email, and LinkedIn; nurture MQLs, schedule meetings with Account Executives, track leads in Pipedrive, and meet monthly quotas.

Conduct outbound prospecting and qualify MQLs via calls, email, and LinkedIn; schedule meetings with Account Executives; manage leads in Pipedrive; build relationships with prospects and AWS contacts; meet monthly quotas and daily outbound targets; obtain AWS Cloud Practitioner certification within first 30 days.

Design, build, and maintain resilient AWS cloud infrastructure and production Kubernetes clusters. Automate infrastructure with IaC and CI/CD, ensure security/compliance, monitor systems, troubleshoot issues, and mentor junior DevOps engineers while working directly with customers and stakeholders.

Design, build, and maintain AWS cloud infrastructure and production Kubernetes clusters using IaC and CI/CD. Implement monitoring, security, automation, troubleshoot issues, and mentor junior DevOps engineers while working with customers and stakeholders.

Design, build, and maintain resilient AWS cloud infrastructure and production Kubernetes clusters. Implement infrastructure-as-code and CI/CD, automate operations, enforce security/compliance, monitor systems, troubleshoot issues, and mentor junior DevOps engineers while working with customers and stakeholders.

Design, develop, test, deploy, and support scalable AWS-based applications across frontend and backend technologies. Build APIs and microservices, manage databases, implement security and compliance measures, debug code, participate in code reviews, and collaborate with product, design, and operations teams. The role requires strong full-stack development experience, cloud expertise, independent work ability, and effective English communication.

Drive new revenue by co-selling with AWS teams to identify, qualify, and close cloud and managed services opportunities. Build relationships with AWS sellers and customers, scope complex engagements with solutions architects, maintain pipeline and forecasts, represent Cloudelligent at AWS and customer meetings, and ensure smooth handoffs to delivery for long-term customer success.

Generate and qualify outbound B2B leads for AWS cloud services via calls, emails, and LinkedIn; manage leads in Pipedrive; book meetings for Account Executives; meet monthly quotas; maintain AWS relationships and nurture interested prospects.

Generate and qualify outbound B2B leads for AWS cloud services via cold calling, email, and LinkedIn. Nurture MQLs, book meetings with Account Executives, track activity in Pipedrive, maintain AWS relationships, meet quotas, and obtain AWS Cloud Practitioner certification within 30 days.

Drive new revenue by co-selling with AWS teams: identify, qualify, and close cloud and managed-services opportunities; build AWS seller and customer relationships; scope engagements with solutions architects; maintain pipeline and forecasts; represent Cloudelligent in AWS and customer meetings; ensure smooth handoff to delivery for long-term success.

Design, implement, and optimize enterprise Amazon Connect contact center solutions using AWS serverless services and conversational AI. Integrate with CRMs and contact center platforms, develop automation and analytics, support architecture, workshops, and GTM activities.

Design, implement, and optimize enterprise Amazon Connect contact center solutions using AWS serverless services and conversational AI. Configure Connect components, integrate with CRMs and enterprise platforms, develop serverless extensions, implement Lex/Bedrock-based NLP, enable analytics and Contact Lens, troubleshoot performance/security, and support architecture workshops, POCs, and GTM initiatives.

Design, implement, and optimize enterprise Amazon Connect contact centers using AWS serverless services and conversational AI. Integrate Connect with CRMs and enterprise platforms, develop Lambda/API-driven extensions, configure contact flows and analytics, troubleshoot performance and security, and support architecture workshops, GTM initiatives, and customer demos.

Design and implement scalable AWS cloud architectures focused on modernization, data engineering, and Generative AI/ML. Lead presales, migrate legacy apps, build data pipelines, define governance and security, and collaborate across teams to deliver Well-Architected solutions.

Design and implement scalable AWS cloud architectures that integrate data engineering and AI/ML (including Generative AI). Lead app and data modernization, migrations, presales architecture, Well-Architected reviews, governance for security/compliance, and knowledge transfer to delivery teams. Drive use of SageMaker/Bedrock, data pipelines, containerization, and infrastructure-as-code for multi-region deployments.

Lead design, implementation, optimization, and deployment of AI solutions on AWS. Fine-tune pre-trained models, apply RAG and vector DB techniques, reduce hallucination, use AWS data services, integrate OpenAI/Azure OpenAI, and lead an AI engineering team while collaborating cross-functionally.

Lead design, fine-tuning, optimization, and deployment of AWS-based AI solutions. Use AWS AI and data services, RAG and vector search (pgvector), reduce hallucinations, apply prompt engineering, and guide a team to integrate AI into products while staying current on AI advancements.

Lead development, optimization, and deployment of AWS-based AI solutions. Fine-tune pre-trained models, implement RAG and vector search (pgvector), reduce hallucinations, integrate AI services (SageMaker, Bedrock, OpenAI), and manage a team to deliver scalable, production-ready AI features.