Senior Developer - Enterprise Integration

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)