The Cloud Migration Architect will lead the delivery of advanced solutions in application development, platform engineering, and data engineering. They are responsible for managing workload migrations from on-premise data centers to AWS while ensuring security and compliance.
You will lead strategic sales initiatives for CCaaS and CX transformation programs by leveraging advanced AI and cloud technologies. The role involves managing end-to-end sales cycles, defining customer transformation roadmaps, and collaborating with technical teams to deliver AI-driven business outcomes.
Design, build, and scale robust platform services, APIs, and microservices while driving architectural decisions for healthcare platforms. Collaborate with product and clinical teams to ensure system reliability, performance, and quality through modern engineering practices.
The Associate Architect will lead the end-to-end development lifecycle, designing and building scalable web applications using Java and Spring Boot. They will also perform deep-system analysis, troubleshoot complex technical issues, and ensure high-quality code through test-driven development and AI-augmented tools.
The Associate Architect will design, build, and optimize scalable web applications using a Java-based microservices architecture. They will lead the full software development lifecycle, collaborating with stakeholders to deliver high-performing, maintainable code.
Design and implement enterprise-grade Generative AI solutions using AWS Bedrock and Agentcore. Orchestrate agentic AI workflows and manage RAG pipelines to ensure scalable, high-performance AI applications.
The Technical Architect will design and implement enterprise-grade MLOps and LLMOps strategies, including model training, deployment, and monitoring pipelines. They will serve as a technical authority, guiding cross-functional teams and ensuring all solutions meet scalability, security, and governance standards.
The Technical Architect will lead platform engineering initiatives and manage large-scale workload migrations from on-premise data centers to AWS. They are responsible for designing optimal migration strategies, executing lift-and-shift or replatforming tasks, and ensuring seamless transitions for client infrastructure.
Develop and integrate GenAI and LLM-based solutions into large-scale cloud-based SaaS production environments for healthcare. Lead technical architecture design, mentor senior team members, and collaborate across functions to deliver high-impact business outcomes.
You will act as a technical advisor to design end-to-end AI solutions and shape long-term technology roadmaps for strategic clients. Additionally, you will own the technical sales cycle, from discovery and pitching to securing high-value enterprise deals.
Lead the origination and closure of large-scale enterprise AI transformation engagements within the power, utilities, and energy sectors. Serve as a strategic advisor to C-suite executives while managing P&L and driving portfolio growth through local market dominance.
Lead enterprise application migration and modernization initiatives to AWS using rehost, replatform, and refactor strategies. Design and implement cloud-native architectures while providing technical leadership and mentorship to development teams.
Design and implement scalable infrastructure for GenAI and LLM workloads across multi-GPU environments. Collaborate with cross-functional teams to optimize performance and support production-grade AI deployments.
Design and optimize scalable infrastructure for GenAI and LLM workloads across multi-GPU environments. Collaborate with cross-functional teams to manage compute-intensive jobs and deploy production-grade AI solutions.
Lead the architectural vision for a next-generation data layer specifically designed for Agentic AI workflows. Act as the primary technical liaison for customers while overseeing the health, security, and performance of complex hybrid-database environments.
The Architect Machine Learning Engineer will design and deploy production-grade agentic AI systems and multi-agent workflows from the ground up. They are responsible for implementing scalable orchestration layers, managing state, and ensuring robust deployment on major cloud platforms.
Design and optimize scalable infrastructure for GenAI and LLM workloads across multi-GPU environments. Manage compute-intensive jobs using Slurm and Kubernetes while building production-grade GenAI pipelines.
Drive the technical strategy and execution of the AWS AI/ML business, including leading pre-sales discussions and creating technical proposals. The role involves collaborating with AWS leadership to develop packaged offerings and delivering complex AI/ML customer engagements.
Drive strategic growth, revenue, and profitability for a portfolio of major P&C Insurance enterprise accounts. Build executive-level relationships to implement AI, data, and cloud transformation solutions that improve business outcomes.
Develop and execute comprehensive organizational change management strategies and communication plans for large-scale cloud migrations. Lead stakeholder engagement, training enablement, and readiness assessments to ensure successful technology adoption.
Lead strategic cloud migration roadmaps and conduct technical assessments of on-premise VMware infrastructure. Design robust cloud network security frameworks and oversee the execution of migrating complex workloads to public cloud platforms.
Drive revenue growth and customer acquisition within the AWS Public Sector segments, including Higher Education and Government. Lead sales strategies, manage complex sales cycles, and build executive relationships within the AWS ecosystem.
Architect and implement enterprise-grade MLOps and LLMOps strategies and pipelines using GCP-native services. Serve as a technical authority to design scalable ML platforms and mentor engineers on best practices.
Architect and build full-stack, enterprise-grade platforms using modular agentic workflow patterns. Design and implement intelligent workflows while ensuring system security, scalability, and seamless enterprise integration.
Design and optimize scalable infrastructure for GenAI and LLM workloads across multi-GPU environments. Collaborate with cross-functional teams to deploy models and manage compute-intensive jobs using Slurm and Kubernetes.
