Associate Software Architect AI Solutions

Siemens

7 - 12 years

19 - 25 Lacs

bengaluru

Posted:1 day ago| Platform:

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Skills Required

documentation nfrs aiml artificial intelligence ml kubernetes algorithms python regression testing smoke testing microsoft azure docker java ecs system architecture electricians mysql agile aws ejb sdlc java servlets java web services

Work Mode

Work from Office

Job Type

Full Time

Job Description

Youll make an impact by:

Collaborate with AI/ML engineers, developers, and platform architects to define end-to-end solution architectures for AI-powered systems
Design and review architectures that support LLM-based, Deep Learning, and traditional ML workloads with an emphasis on modularity, performance, and maintainability.
Drive architectural alignment across components such as model serving, orchestration layers, data pipelines, and cloud infrastructure.
Incorporate Non-Functional Requirements (NFRs) including scalability, testability, observability, latency, and fault tolerance into system designs.
Define architecture patterns for deploying models as microservices, integrating with APIs, and ensuring CI/CD readiness.
Evaluate and recommend suitable cloud services and managed tools from AWS (Sagemaker, Bedrock) and Azure (ML Studio, OpenAI, AI Foundry).
Ensure high standards of code quality, performance benchmarking, and architectural documentation.
Collaborate in technical reviews and mentor engineering teams on architectural best practices and trade-offs.

Use your skills to move the world forward!

Bachelors or Masters degree in Computer Science, Engineering, or a related technical field.
7+ years of experience in software/system architecture, including at least 4 years working with AI/ML-based solutions.
Strong understanding of AI system lifecycle, including model development, serving, monitoring, and retraining.
Experience designing scalable systems with Python, FastAPI, containerization (Docker), and orchestration (Kubernetes or ECS).
Proficiency in defining and measuring NFRs, conducting architectural performance reviews, and supporting DevOps and MLOps practices.
Solid hands-on experience with cloud-native AI development using AWS or Azure tools and services
Experience working in AI/ML-driven environments, especially with LLMs, RAG architectures, and agent-based systems.
Familiarity with model observability, logging frameworks, and telemetry strategies for AI
applications.
Prior exposure to architecture in the Power/Energy or Electrification domain is a strong plus.
Good understanding of hybrid system architectures that integrate real-time and batch
pipelines.
Strong collaboration and documentation skills with the ability to align cross-functional technical teams.

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