About this role
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)