Sr. lead dotnet developer Jobs

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Architect - Dotnet

Neurealm
Chennai, Tamil Nadu

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Job details

Full-time
₹35,00,000 - ₹45,00,000 a year
13 hours ago

Qualifications

Live chat
Azure
Cloud architecture
Law
ASP.NET Core
Kubernetes
.NET Core
C#
System design
Git
.NET
Master's degree
SQL
OS Kernels
AWS
Docker
Terraform
Azure Certification
REST
GitHub
APIs
Cloud computing
S3
DynamoDB
AI
RDS database
gRPC
Entity Framework
AWS Certified Solutions Architect – Professional
SDLC
Design patterns

Full job description

Job Description: Application Architect (.NET + Multi-Cloud: AWS & Azure)

Role Overview

We are seeking a highly skilled, forward-thinking Application Architect with a deep background in the .NET ecosystem, proven expertise in designing multi-cloud topologies (AWS and Azure), and a strong proficiency in integrating Artificial Intelligence (AI) workflows into enterprise applications.

In this senior position, you will bridge the gap between complex business requirements and modern, scalable cloud technology. Beyond traditional architecture, you will champion the adoption of Generative AI capabilities, optimize developer productivity using AI-assisted tools like GitHub Copilot, drive monolithic-to-microservices migrations, and instill absolute best practices across our engineering teams.

Key Responsibilities

Architecture & System Design

Enterprise Blueprinting: Architect end-to-end, highly available, fault-tolerant enterprise applications leveraging .NET Core / .NET 8+ deployed into hybrid, multi-cloud structures (AWS and Azure).
Modernization: Lead strategic initiatives to decompose legacy .NET monolithic architectures into containerized, cloud-native microservices and event-driven topologies.
Pattern Implementation: Mandate and implement Domain-Driven Design (DDD), SOLID principles, CQRS, and asynchronous event-driven design patterns.

AI Integration & Developer Productivity

AI Architecture: Design and integrate AI/ML capabilities into microservice ecosystems, utilizing cloud-native AI services (e.g., Azure OpenAI, AWS Bedrock) safely while ensuring strict data privacy and model governance.
GenAI & Orchestration: Architect solutions utilizing LLMs, Retrieval-Augmented Generation (RAG), and agentic automation using frameworks compatible with .NET (e.g., Microsoft Semantic Kernel, LangChain).
AI-Driven Development Advocacy: Champion the use of AI-assisted engineering tools. Define governance, prompt engineering standards, and best practices for leveraging GitHub Copilot to accelerate the team's software development lifecycle (SDLC) while ensuring code quality and compliance.

Multi-Cloud & DevOps Engineering

Cloud Strategy: Design solutions optimized for both AWS and Azure, advising the business on cost-efficiency, platform trade-offs, and portability.
Managed Services Mastery: Architect utilizing cloud-native offerings across both ecosystems:

o AWS Stack: EC2, ECS/EKS, Lambda (Serverless), S3, API Gateway, DynamoDB, RDS.

o Azure Stack: AKS, Azure Functions, App Services, Azure SQL, CosmosDB, Service Bus.

Infrastructure as Code (IaC): Establish declarative environments using Terraform or CloudFormation / Azure Bicep to support automated blue/green or canary deployment structures.

Technical Leadership & Governance

Mentorship & Quality: Conduct strict code and architecture reviews, acting as a direct mentor to senior and staff engineers to elevate the overall technical capacity of the group.
Documentation & Standards: Author pristine Low-Level Designs (LLD) and High-Level Designs (HLD), defining explicit technical templates for standardizing cross-team execution.

Required Technical Qualifications

Experience: 8+ years of professional experience in software engineering, with a minimum of 3+ years acting as a dedicated Technical/Application Architect in enterprise environments.
Core .NET Tech Stack: Advanced expertise in C#, .NET Core/.NET 8+, ASP.NET Core Web API, Entity Framework Core, gRPC, and RESTful API management.
Cloud Computing: Hands-on architecture experience in both AWS and Azure. Broad understanding of when to use computing vs. serverless vs. managed container services on both hyperscalers.
AI Skills: Proven experience implementing Generative AI features, consuming LLM APIs, and utilizing vector databases (e.g., Pinecone, Qdrant, Azure Cosmos DB vector search).
Containers & Orchestration: Deep expertise in Docker, Kubernetes (EKS and AKS), and service mesh concepts.

Preferred Qualifications & Certifications

AI-Assisted Tools: Practical experience using GitHub Copilot (or Copilot Chat) to write code, generate tests, and refactor applications. Experience configuring Copilot at an enterprise level is a massive plus.
Hyperscaler Certifications: AWS Certified Solutions Architect – Professional and/or Microsoft Certified: Azure Solutions Architect Expert.
AI Certifications: Microsoft Certified: Azure AI Engineer Associate or equivalent AWS AI certifications.

Core Competencies & Workplace Skills

Strategic Communicator: Outstanding capability to abstract deep technical concepts (including complex AI and cloud structures) for executive audiences while interacting fluidly with technical engineers.
Blocker Remediation: Proactive problem solver who surfaces architectural bottlenecks early, alongside pragmatic remediation vectors.
Autonomous Execution: Deeply trusted partner who functions cleanly with minimal oversight, asserting authority to hold external integration partners accountable.

Job Snapshot

Updated Date

23-06-2026

Job ID

Job_304414

Practice

Engineering Practice

Location

Chennai, Tamil Nadu, India

Experience

15 - 20 Years

Employee Type

Full Time Employee

Salary Range

INR 3500000 - 4500000 (Annual)

Apply Now

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