Jobs at Cloudelligent

Develop, optimize, and deploy AI and machine learning solutions using AWS services, foundation models, RAG, vector databases, and agentic AI frameworks. Lead AI engineers, improve model reliability and performance, integrate AI capabilities into products, and collaborate with technical and non-technical stakeholders. The role also involves prompt engineering, data processing, model evaluation, and adopting emerging AI technologies.

Lead the development, optimization, and deployment of AI solutions using AWS services, generative AI, RAG, vector databases, and machine learning frameworks. Fine-tune models, improve reliability, reduce hallucinations, and integrate AI capabilities into products. Lead AI engineers, manage projects, collaborate with stakeholders, and evaluate emerging technologies. The role also involves prompt engineering, data preprocessing, feature engineering, and scalable model deployment.

Lead the development, optimization, and deployment of AI solutions using AWS services, machine learning frameworks, generative AI, RAG, vector databases, and prompt engineering. Guide AI engineers, integrate AI capabilities into products, improve model reliability, and collaborate with technical and non-technical stakeholders.

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

Build, deploy, and manage resilient AWS cloud infrastructure and production Kubernetes environments. Develop infrastructure-as-code and CI/CD automation, maintain monitoring, logging, security, compliance, and operational procedures, troubleshoot infrastructure issues, collaborate directly with customers, and mentor junior DevOps engineers. The role requires strong expertise in AWS architecture, Kubernetes, Docker, Terraform or CloudFormation, CI/CD tools, configuration management, scripting, networking, and cloud-native security.

Build, deploy, and maintain resilient AWS cloud infrastructure and production Kubernetes environments. Develop infrastructure-as-code and CI/CD automation, manage containers, monitoring, logging, networking, security, and compliance practices, troubleshoot infrastructure issues, collaborate directly with customers, and improve operational procedures. The role also includes independently managing projects and mentoring junior DevOps engineers.

Designs, deploys, and manages resilient AWS cloud infrastructure and production Kubernetes environments. Builds infrastructure-as-code and CI/CD automation, maintains monitoring, logging, security, networking, and operational practices, troubleshoots infrastructure issues, and works directly with customers and stakeholders. The role also independently delivers projects and mentors junior DevOps engineers.

Lead end-to-end data migrations for LegalTech SaaS implementations. Analyze legacy financial and practice-management systems, design mappings and ETL strategies, extract and transform data using SQL and Python, execute test and production migrations, validate results, reconcile financial datasets, resolve data-quality issues, and document technical specifications. Collaborate with project managers, consultants, client IT teams, and non-technical stakeholders while improving automation, templates, and migration best practices.

Lead end-to-end data migration and ETL processes for LegalTech SaaS implementations. Analyze legacy financial and practice-management data, map schemas, extract and transform data using SQL and Python, execute dry runs and production loads, validate accuracy, reconcile results, resolve data-quality issues, and document migration specifications. Collaborate with project managers, implementation consultants, client IT teams, and non-technical stakeholders while improving migration automation and best practices.

Designs, implements, and optimizes enterprise Amazon Connect contact center solutions using AWS serverless services, conversational AI, REST APIs, and enterprise integrations. Configures contact flows, routing, queues, analytics, recording, and agent workspaces; troubleshoots deployments for scalability, reliability, and security. Collaborates with customers and technical teams on requirements, architecture, workshops, demonstrations, proof-of-concepts, proposals, and go-to-market initiatives.

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.