Dotnet Architect

Tarento Group; Bengaluru; On-site; INR 3,000,000 - 7,000,000; Full time

Job summary

Tarento Group in Bengaluru seeks a Senior Technical Architect with deep expertise in .NET, cloud-native architecture, distributed and event-driven systems, and AI-native engineering to lead the design and evolution of highly scalable, secure platforms.

You will drive architecture and technical strategy, mentor engineers, review designs, and partner with DevOps for CI/CD, observability, and AI-first practices across the SDLC, while staying hands-on to validate key decisions.

Qualifications

• 10+ years in software engineering, including architectural leadership.

Responsibilities

• Define end-to-end architecture for large-scale .NET systems in cloud-native environments.
• Lead cross-team technical decisions and review high-risk designs.
• Drive CI/CD, observability, and security practices across the SDLC.
• Mentor senior engineers and steer teams toward AI-native engineering.

Skills

Architectural leadership

.NET

Cloud-native

Distributed systems

AI native engineering

Tools

Kubernetes

Azure DevOps

Job description

About Tarento

Tarento is a fast-growing technology consulting company headquartered in Stockholm, with a strong presence in India and clients across the globe. We specialize in digital transformation, product engineering, and enterprise solutions, working across diverse industries including retail, manufacturing, and healthcare. Our teams combine Nordic values with Indian expertise to deliver innovative, scalable, and high-impact solutions.

We're proud to be recognized as a Great Place to Work, a testament to our inclusive culture, strong leadership, and commitment to employee well-being and growth. At Tarento, you’ll be part of a collaborative environment where ideas are valued, learning is continuous, and careers are built on passion and purpose.

Technical Architect – .NET (Cloud, Distributed Systems& AI Native Engineering)

Experience

• 10+ years in software engineering, including architectural leadership.

We are seeking an experienced Senior Technical Architect with deep expertise in .NET, cloud-native architecture, distributed systems, event-driven architecture, and AI Native Engineering to lead the design and evolution of highly scalable, secure, and resilient platforms.

This role focuses on system architecture, technical strategy, and cross-team leadership while remaining hands‑on enough to validate designs and guide implementation. Strong experience in distributed systems and event-driven architecture is essential. Kubernetes and specific messaging platforms are beneficial but not mandatory. Experience with Agentic AI and applying AI across the SDLC is highly desirable.

Key Responsibilities

Architecture & Design

• Define end-to-end solution architecture for large-scale .NET systems in cloud-native environments.
• Design microservices-based and distributed architectures aligned with business goals.
• Establish reference architectures, patterns, and best practices.
• Evaluate and select technologies, frameworks, AI platforms, and engineering tools.

Technical Leadership

• Act as a technical authority across multiple teams.
• Review and approve architectural designs and high-risk technical changes.
• Guide teams on scalability, resilience, performance, security, and AI-first engineering practices.
• Mentor senior engineers and emerging architects.
• Drive engineering teams towards becoming more AI-native by leveraging AI throughout the SDLC.

Cloud, Platform & DevOps Strategy

• Define architectural guidance for containerized and cloud-based deployments.
• Provide direction on Kubernetes-based platforms (experience or strong conceptual understanding).
• Collaborate with DevOps/SRE teams on CI/CD strategy using Azure DevOps.
• Ensure observability standards (logging, monitoring, tracing) are in place.

AI Native Engineering

• Design or enhance enterprise applications using AI Agents and Agentic workflows.
• Build or integrate solutions using Model Context Protocol (MCP) and Agent-to-Agent (A2A) communication patterns.
• Apply AI capabilities across the SDLC to improve development, testing, documentation, and operational efficiency.
• Understand LLM Token Economics, including token usage optimization, context management, latency, and cost optimization.
• Evaluate and recommend AI frameworks and tooling for enterprise adoption.