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Job Title: Cloud Engineering Manager – API
Job Summary:
We are seeking a highly experienced Cloud Engineering Manager – API, Full Stack & AI/ML with 12+ years of strong experience in cloud engineering, enterprise application development, API-led architecture, Full Stack development, and AI/ML solution delivery across multi-cloud environments. The role focuses on leading the design, development, and modernization of cloud-native applications, enterprise API ecosystems, and AI-powered business solutions to drive digital transformation, innovation, and operational excellence for enterprise clients.
The ideal candidate will possess deep technical expertise combined with strong consulting and stakeholder management capabilities, with the ability to lead large engineering teams, define technology roadmaps, drive AI/ML adoption, and deliver scalable cloud and API solutions across complex enterprise landscapes.
Key Responsibilities:
- Lead the architecture, design, development, and modernization of cloud-native applications, enterprise API platforms, and AI-powered solutions across Azure, AWS, and GCP environments.
- Define and execute API-first, cloud-native, and platform engineering strategies aligned with enterprise digital transformation objectives.
- Establish engineering standards, governance frameworks, architecture best practices, and reusable technology accelerators across application development initiatives.
- Drive adoption of modern application architectures including microservices, event-driven systems, containerized platforms, and serverless technologies.
- Lead full-stack application development using modern frontend and backend frameworks with Python as the primary development language.
- Strong competency in enterprise API design, development, integration, lifecycle management, security, and governance using API Management platforms.
- Drive implementation of enterprise integration solutions leveraging REST APIs, GraphQL, event streaming, and hybrid cloud integration patterns.
- Lead development and operationalization of AI/ML, Generative AI, Large Language Models (LLMs), RAG architectures, AI Agents, and intelligent automation solutions.
- Collaborate with data science, cloud, platform, and business teams to integrate AI capabilities into enterprise applications and business processes.
- Define AI engineering best practices including Responsible AI, MLOps, security, observability, governance, and lifecycle management.
- Drive cloud application modernization initiatives utilizing Kubernetes, Containers, DevSecOps, Platform Engineering, and Infrastructure as Code.
- Lead Proof of Concepts (PoCs), innovation initiatives, solution accelerators, and technology assessments for Cloud, API, and AI transformation programs.
- Develop business cases, executive dashboards, technology roadmaps, and solution recommendations for client engagements.
- Collaborate with Architecture, Security, Data, DevOps, and Platform teams to align technology initiatives with enterprise governance and operational objectives.
- Support pre-sales opportunities, solutioning workshops, RFP responses, technical proposals, and strategic consulting engagements.
Qualifications:
- 12+ years of experience in Cloud Engineering, Enterprise Application Development, API Engineering, Full Stack Development, and Technology Delivery.
- 5+ years of experience leading engineering teams, architecture programs, and large-scale cloud transformation initiatives.
- Strong understanding of cloud-native architecture principles including microservices, serverless computing, event-driven architecture, and distributed systems.
- Proven expertise in API strategy, API governance, integration architecture, and enterprise modernization initiatives.
- Strong experience leading AI/ML and Generative AI solution development and enterprise adoption programs.
- Experience working in client-facing consulting, advisory, or enterprise transformation roles.
- Strong understanding of cloud security, application security, governance, compliance, DevSecOps, and operational excellence practices.
- Excellent leadership, communication, stakeholder management, and problem-solving skills.
- Bachelor’s degree in Information Technology, Computer Science, Engineering, or a related discipline.
- Master’s degree preferred.
Technical Expertise:
- Strong expertise in Cloud Platforms including Microsoft Azure, Amazon Web Services (AWS), and Google Cloud Platform (GCP).
- Deep hands-on experience in Python, FastAPI, Flask, Django, and backend service development.
- Strong Full Stack development expertise using https://jobeax.com/link/6WcBICn0LM558SP0, Angular, https://jobeax.com/link/JSd7UYCSg572jJDY, TypeScript, and JavaScript.
- Strong competency in designing and implementing REST APIs, GraphQL services, Microservices, and Enterprise Integration frameworks.
- Experience with API Management platforms including Apigee, Kong, Azure API Management, MuleSoft, or equivalent solutions.
- Strong knowledge of Event-Driven Architecture, Kafka, RabbitMQ, and enterprise messaging platforms.
- Proven expertise in AI/ML technologies including Azure OpenAI, OpenAI APIs, AWS Bedrock, Vertex AI, LangChain, Semantic Kernel, and MLOps.
- Strong competency in developing solutions using LLMs, RAG Architectures, AI Agents, Prompt Engineering, Embeddings, and Vector Databases.
- Experience with containerization and orchestration platforms including Docker, Kubernetes, and OpenShift.
- Strong competency in DevSecOps, CI/CD, GitOps, Platform Engineering, and Infrastructure as Code using Terraform, Azure DevOps, GitHub Actions, Jenkins, and ArgoCD.
- Experience with relational, NoSQL, and vector databases including PostgreSQL, SQL Server, MongoDB, Cosmos DB, Redis, Pinecone, ChromaDB, and FAISS.
- Strong understanding of Observability, Application Performance Monitoring, Logging, Security Monitoring, and Site Reliability Engineering practices.
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