Sr Developer - Enterprise Integration

Job description

Title: Lead Integration Developer Exp: 9–12 Years Role Summary A strategic and hands-on Integration Leader responsible for driving end-to-end delivery of enterprise integration solutions. Ensures alignment with enterprise architecture, leads technical design (HLD/LLD), and builds high-performing teams while leveraging modern cloud, AI, and Copilot-enabled development capabilities. Key Responsibilities Integration Architecture & Delivery Own and lead end-to-end integration solution design and delivery across complex enterprise programs. Define and implement integration architectures, API strategies, and reusable frameworks aligned with enterprise standards. Create, review, and govern High-Level Designs (HLDs) and Low-Level Designs (LLDs) ensuring scalability, performance, and maintainability. Drive architecture governance, technical design reviews, and best practices adoption . Azure Integration Services Implementation Lead development using Azure Logic Apps, Azure Functions, Azure Data Factory , and broader Azure Integration Services. Design highly resilient, secure, and scalable workflows and orchestrations . API Management & Governance Design, publish, secure, and monitor APIs via Azure API Management (APIM) . Drive enterprise API governance , lifecycle management, versioning, and security standards. Messaging & Event-Driven Architecture Build and implement event-driven and asynchronous architectures using Azure Service Bus, Event Grid, and Event Hubs . Champion loosely coupled, scalable integration patterns . Hybrid Integration Architect and implement integrations between on-premises systems and cloud platforms , ensuring seamless and reliable connectivity. AI & Copilot-Driven Engineering Leverage Microsoft Copilot (GitHub Copilot, M365 Copilot) to improve developer productivity, accelerate code development, and enhance solution quality. Utilize Generative AI for: Automated code generation, refactoring, and documentation (LLDs, API specs) Intelligent workflow design and optimization AI-assisted debugging, testing, and root cause analysis Integrate AI-powered services (Azure OpenAI, Cognitive Services) within integration solutions to enable intelligent data processing and decision-making. Promote AI-first engineering practices , including prompt engineering and responsible AI usage. Monitoring, Security & Compliance Implement end-to-end observability using Cribl. Ensure secure data handling, compliance, and governance across integration solutions. Technical & Team Leadership Provide strong technical leadership and direction across teams. Conduct design reviews, code reviews, and enforce engineering standards . Mentor team members, enabling skill development in integration, cloud, and AI technologies . Manage technical risks, escalations, and critical design decisions . Collaboration & Stakeholder Management Collaborate with cross-functional teams, architects, business stakeholders, and vendors . Align technology solutions with business goals and enterprise strategy . Build and nurture a high-performing, collaborative, and innovation-driven integration team . Required Skills Experience: 9–12+ years in software engineering with strong focus on cloud and iPaaS integrations . Azure Expertise: Deep hands-on experience with Azure Integration Services (AIS) . Development Skills: Strong proficiency in C#, .NET, REST/SOAP APIs, JSON, XML . Design Skills: Extensive experience in LLD/HLD creation, architecture design, and solution documentation . API Expertise: Strong experience in API architecture, governance, and lifecycle management . Integration Patterns: Expertise in event-driven, microservices, and hybrid integration architectures . AI & Copilot Skills: (Good to have) Hands-on usage of GitHub Copilot / M365 Copilot for development acceleration Understanding of prompt engineering and AI-assisted development workflows Exposure to Azure OpenAI / AI services integration Delivery Experience: Proven experience leading large-scale enterprise integration delivery . Preferred Skills Experience with MuleSoft architecture / coexistence strategies . Exposure to advanced AI/ML integration use cases and intelligent automation . Knowledge of data transformation standards (EDI, XML, JSON) and large-scale data pipelines. Familiarity with AI governance, ethics, and secure AI adoption in enterprises . Preferred Certifications Azure Solutions Architect Expert (AZ-305) Azure Developer Associate (AZ-204) DevOps Engineer Expert (AZ-400) (Good to have) Azure AI Engineer Associate (AI-102)