New opportunity

Senior AI & Full Stack Software Engineer – Cloud & AI Accelerator Team

SimCorp · Hyderabad, India

About this role

SimCorp is seeking a Senior AI & Full Stack Software Engineer to join its newly established Cloud & AI Accelerator team in Hyderabad. The role focuses on helping accelerate high-impact, strategic initiatives, exploring AI and cloud opportunities, and supporting important business solutions.

Responsibilities

Help explore how AI can improve user experiences, workflows, and engineering productivity.
Build AI agents for and in collaboration with different business domains.
Design, develop, test, and maintain AI agents & modern cloud-based applications across the full stack.
Collaborate closely with other engineers, product stakeholders, UX designers, and architects to shape solutions that solve real user problems.
Contribute to frontend and backend development using technologies such as .NET, TypeScript, and Angular.
Participate in discovery, experimentation, and iterative product development.
Build scalable and maintainable solutions with a strong focus on quality, testing, and operational excellence.

Required qualifications

Experience as a software engineer working with both frontend and backend technologies.
Experience with modern frontend development using frameworks such as Angular and TypeScript.
Experience with C#, .NET, and cloud-based development.
Passion for AI and some experience implementing AI agents.

Preferred qualifications

Experience with React or similar frontend frameworks.
Experience with Azure, distributed systems, micro frontends, or investment management workflows.

Benefits

Global hybrid work policy allowing remote work on certain days and two days from the office.
Every 6th sprint reserved for planning, innovation, and learning new skills.
High degree of self-organization, freedom, and empowerment in planning and designing work.

For full details about this role, click “Apply on company site” to view the employer’s original posting.

Skills for this role

Azure.NETTypeScriptAngularC#Claude CodeReact

Checking your profile…

Preparation suggestions, not the employer’s actual interview questions. Always check the original posting for current requirements.

Understand the role

What matters most

Building and Integrating AI Agents
Design, develop, test, and maintain AI agents in collaboration with different business domains to explore how artificial intelligence can improve user experiences, workflows, and overall engineering productivity.
Full-Stack Cloud Application Development
Contribute to both frontend and backend development using technologies such as Azure, .NET, TypeScript, and Angular to build scalable, maintainable, and high-quality cloud-based applications.
Cross-Functional Collaboration
Work closely with engineers, product stakeholders, UX designers, and architects during discovery, experimentation, and iterative product development to shape solutions that solve real user problems.

Likely challenges to think through

Balancing Rapid Experimentation with Production Stability
The Cloud & AI Accelerator team focuses on speed, innovation, and strategic initiatives using AI-assisted workflows like Claude Code. A key difficulty is maintaining rigorous engineering standards, testing, and operational excellence while iterating quickly on exploratory AI agent features. Prepare by reviewing best practices for safely deploying experimental LLM and agentic systems into enterprise cloud architectures.

Practice your answers

Technical practice

Designing Multi-Agent Architectures

What to coverDiscuss how you design autonomous AI agents to collaborate across different business domains. Address communication patterns, state management, and error handling when an agent fails to complete a delegated task.

Full-Stack Development with .NET and Angular

What to coverExplain how you structure a modern enterprise application using C# .NET on the backend and Angular on the frontend. Discuss dependency injection, API design, and type safety across the full stack using TypeScript.

Cloud-Based Deployment and Scalability on Azure

What to coverDescribe your approach to deploying and scaling cloud-native applications on Microsoft Azure. Address containerization, managed services, and strategies for ensuring high availability and fault tolerance.

Integrating AI Assistants into Development Workflows

What to coverExplain how you incorporate AI-assisted development tools like Claude Code into your daily coding practices. Discuss how you balance productivity gains with code quality, security reviews, and unit testing.

State Management and Micro Frontends

What to coverDiscuss the architectural considerations when implementing micro frontends alongside Angular or React. Address shared state management, routing, and independent deployability.

Evaluating AI Agent Performance and Reliability

What to coverDescribe how you test and evaluate AI agents for accuracy, determinism, and safety. Discuss metrics, logging strategies, and handling hallucinations or unexpected tool-calling outputs.

Distributed Systems Resilience and Error Recovery

What to coverExplain patterns used to build resilient distributed systems in the cloud, such as retry policies, circuit breakers, and asynchronous messaging queues using .NET.

Optimizing User Experience for AI-Driven Workflows

What to coverDiscuss how you collaborate with UX designers to present complex AI agent outputs and recommendations to end users cleanly and transparently. Address latency management and streaming responses.

Behavioural practice

Collaborating Across Cross-Functional Teams

What to coverDescribe a situation where you had to work closely with product stakeholders, architects, and UX designers to shape a complex solution. Explain how you aligned differing priorities and ensured a successful delivery using the STAR method.

Navigating Ambiguity in R&D or Accelerator Initiatives

What to coverTell me about a time you joined a newly established team or worked on a fast-paced initiative with ambiguous requirements. Detail how you approached discovery, experimentation, and iterative development.

Balancing Innovation with Operational Excellence

What to coverProvide an example of how you maintained high quality, testing standards, and scalability while pushing for speed and innovative features under tight timelines.

Learning and Adapting to New Technologies

What to coverDescribe a project where you had to quickly adopt a new framework, tool, or cloud service. Explain your learning process, how you leveraged self-direction, and the impact it had on your team.

Sharpen your knowledge

Topics to prepare

AI Agent Architecture and Workflows
Review concepts of autonomous agents, multi-agent orchestration, and prompt/response loops. Relevance: The role explicitly requires building AI agents for and in collaboration with different business domains to improve workflows and user experiences.
Cloud-Based Distributed Systems
Study cloud scalability patterns, micro frontends, and distributed backend services. Relevance: The posting highlights designing and maintaining cloud-based applications and mentions preferred experience with distributed systems and Azure.
AI-Assisted Development Workflows
Understand how developer productivity tools and LLM coding assistants operate within modern engineering practices. Relevance: The team actively explores AI-assisted workflows using tools like Claude Code to support experimentation and learning.

Skills to revise

C# and .NET Development
Practice building robust backend services, APIs, and business logic using C# and the .NET framework. Relevance: Explicitly required for full-stack and backend development in the Cloud & AI Accelerator team.
TypeScript and Angular
Build modern, typed frontend user interfaces and components using TypeScript and Angular. Relevance: Required for frontend development, with React listed as a valuable secondary framework.
Microsoft Azure Cloud Services
Familiarize yourself with deploying, managing, and scaling applications on Azure. Relevance: Azure is listed as a core technology stack item for cloud-based development.

Your preparation checklist

Build a Sample AI Agent Proof-of-Concept
Develop a working prototype of an AI agent that integrates with an external business domain or API, demonstrating orchestration, tool-calling, and error handling.
Create a Full-Stack .NET and Angular Application
Build a small end-to-end web application using C#, .NET for the backend services and TypeScript with Angular for the frontend UI, incorporating responsive design and clean architecture.
Prepare Cloud Architecture and Deployment Artifacts
Outline a deployment strategy for hosting a cloud-native full-stack application on Microsoft Azure, covering containerization, scalability, and distributed system considerations.
Assemble Evidence for AI-Assisted Workflow Experience
Document examples of how you use AI-assisted development tools like Claude Code or similar coding assistants to accelerate experimentation and boost developer productivity.
Draft Cross-Functional Collaboration Case Studies
Prepare specific examples using the STAR method that demonstrate how you have partnered with UX designers, architects, and product stakeholders to solve user-centric problems.
Formulate Strategic Questions for the Employer
Prepare thoughtful questions regarding the Cloud & AI Accelerator team's strategic initiatives, innovation sprints, and how they balance rapid prototyping with operational excellence.

Availability last checked: 4 Nov 2026. Status can change after a check; confirm on the employer’s website. Report an issue · Our checking policy

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