
Sr Developer - Enterprise Integration
- AI
- Copilot
- Azure
- Logic Apps
- Azure Functions
- Azure Data Factory
- Event-Driven Architecture
- M365
- Machine Learning
- Azure OpenAI
- C#
- .NET
- SOAP
- JSON
- XML
- Microservices
- MuleSoft
- AI/ML
- EDI
- Devops
- Azure AI
Title: Lead Integration Developer
Exp: 9โ12 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 leadend-to-end integration solution design and delivery across complex enterprise programs.
- Define and implementintegration architectures, API strategies, and reusable frameworks aligned with enterprise standards.
- Create, review, and governHigh-Level Designs (HLDs) and Low-Level Designs (LLDs) ensuring scalability, performance, and maintainability.
- Drivearchitecture governance, technical design reviews, and best practices adoption.
Azure Integration Services Implementation
- Lead development usingAzure Logic Apps, Azure Functions, Azure Data Factory, and broader Azure Integration Services.
- Designhighly resilient, secure, and scalable workflows and orchestrations.
API Management & Governance
- Design, publish, secure, and monitor APIs viaAzure API Management (APIM).
- Driveenterprise API governance, lifecycle management, versioning, and security standards.
Messaging & Event-Driven Architecture
- Build and implementevent-driven and asynchronous architectures usingAzure Service Bus, Event Grid, and Event Hubs.
- Championloosely coupled, scalable integration patterns.
Hybrid Integration
- Architect and implement integrations betweenon-premises systems and cloud platforms, ensuring seamless and reliable connectivity.
AI & Copilot-Driven Engineering
- LeverageMicrosoft Copilot (GitHub Copilot, M365 Copilot) to improve developer productivity, accelerate code development, and enhance solution quality.
- UtilizeGenerative AI for:
- Automated code generation, refactoring, and documentation (LLDs, API specs)
- Intelligent workflow design and optimization
- AI-assisted debugging, testing, and root cause analysis
- IntegrateAI-powered services (Azure OpenAI, Cognitive Services) within integration solutions to enable intelligent data processing and decision-making.
- PromoteAI-first engineering practices, including prompt engineering and responsible AI usage.
Monitoring, Security & Compliance
- Implementend-to-end observability usingCribl.
- Ensuresecure data handling, compliance, and governance across integration solutions.
Technical & Team Leadership
- Provide strongtechnical leadership and direction across teams.
- Conductdesign reviews, code reviews, and enforce engineering standards.
- Mentor team members, enablingskill development in integration, cloud, and AI technologies.
- Managetechnical risks, escalations, and critical design decisions.
Collaboration & Stakeholder Management
- Collaborate withcross-functional teams, architects, business stakeholders, and vendors.
- Aligntechnology solutions with business goals and enterprise strategy.
- Build and nurture ahigh-performing, collaborative, and innovation-driven integration team.
Required Skills
- Experience: 9โ12+ years in software engineering with strong focus oncloud and iPaaS integrations.
- Azure Expertise: Deep hands-on experience withAzure Integration Services (AIS).
- Development Skills: Strong proficiency inC#, .NET, REST/SOAP APIs, JSON, XML.
- Design Skills: Extensive experience inLLD/HLD creation, architecture design, and solution documentation.
- API Expertise: Strong experience inAPI architecture, governance, and lifecycle management.
- Integration Patterns: Expertise inevent-driven, microservices, and hybrid integration architectures.
- AI & Copilot Skills: (Good to have)
- Hands-on usage ofGitHub Copilot / M365 Copilot for development acceleration
- Understanding ofprompt engineering and AI-assisted development workflows
- Exposure toAzure OpenAI / AI services integration
- Delivery Experience: Proven experience leadinglarge-scale enterprise integration delivery.
Preferred Skills
- Experience withMuleSoft architecture / coexistence strategies.
- Exposure toadvanced AI/ML integration use cases and intelligent automation.
- Knowledge ofdata transformation standards (EDI, XML, JSON) and large-scale data pipelines.
- Familiarity withAI 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)
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