Senior Solution Architect - AI
Siemens Energy
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Benefits offered by this job
Job summary
Siemens Energy is seeking a hands-on technical leader to drive design, development, and deployment of production-grade Generative AI across enterprise and industrial domains. You will collaborate with product managers, data scientists, engineers, and stakeholders to translate business needs into scalable, secure AI architectures on cloud platforms.
The role involves architectural decision-making, technical mentorship, solution reviews, and guiding teams from PoC to production, with a focus on
Qualifications
- Master’s degree in Computer Science, Engineering, or related field.
- 8+ years in software engineering/data science with minimum 4+ years in AI roles.
- Proven experience delivering production-grade Generative AI solutions using LLMs.
Responsibilities
- Lead end-to-end architecture and implementation of Generative AI solutions.
- Design scalable cloud-based architectures for AI workloads.
- Build and evolve RAG frameworks and multi-agent systems.
- Provide technical leadership and mentorship to engineering teams.
- Collaborate with product managers to define requirements and milestones.
- Ensure enterprise security, reliability, and performance.
- Identify and mitigate risks for production releases.
- Drive adoption of MLOps for model lifecycle management.
Skills
Education
Tools
Job description
You will work as a hands-on technical leader driving the design, development, and deployment of production-grade Generative AI solutions across enterprise and industrial domains. You will collaborate closely with product managers, data scientists, engineers, and business stakeholders to translate complex business needs into scalable, secure, and reusable AI architectures on cloud platforms. Your day will involve architectural decision-making, technical mentorship, solution design reviews, and guiding teams from proof-of-concept to production.
You will work as a hands-on technical leader driving the design, development, and deployment of production-grade Generative AI solutions across enterprise and industrial domains. You will collaborate closely with product managers, data scientists, engineers, and business stakeholders to translate complex business needs into scalable, secure, and reusable AI architectures on cloud platforms. Your day will involve architectural decision-making, technical mentorship, solution design reviews, and guiding teams from proof-of-concept to production.
- Lead the end-to-end architecture and implementation of Generative AI solutions, from ideation to production deployment.
- Design scalable, reusable cloud-based architectures for AI and GenAI workloads.
- Build and evolve advanced Retrieval-Augmented Generation (RAG) frameworks and multi-agent systems.
- Provide technical leadership and mentorship to engineering teams.
- Collaborate with product managers and stakeholders to define requirements and delivery milestones.
- Ensure solutions meet enterprise standards for security, reliability, and performance.
- Identify and mitigate technical risks to enable smooth production releases.
- Drive adoption of MLOps best practices for model lifecycle management.
- Master’s degree in Computer Science, Engineering, or a related technical field.
- 8+ years of experience in software engineering, data science, with minimum 4+ years' experience in AI-related roles.
- Proven experience delivering production-grade Generative AI solutions using LLMs.
- Strong expertise in Python and modern AI/ML frameworks.
- Hands-on experience with RAG, multi-agent, and graph-based AI architectures.
- Experience with Azure OpenAI, AWS SageMaker is must.
- Strong background in MLOps platforms such as MLflow and Kubeflow
- DevOps experience in OpenShift will be a major advantage.
- Experience with API design using FastAPI.
- Knowledge of SQL, NoSQL, and vector databases.
- Excellent communication and stakeholder management skills
Our Transformation of Industry division is decarbonizing the industrial sector. Increasing electrification and efficiency are key, and demand for green hydrogen and derivative fuels will rise. We enable the decarbonization of the industrial sector and the transition to sustainable processes by building on a strong industrial customer base, a global network, diverse technologies, and integrated execution capabilities.
The Data & Artificial Intelligence team develops and operates digital and AI solutions that support business transformation. The team brings together AI engineering, data, cloud, architecture, and software development capabilities to convert business requirements into secure, scalable, and operational solutions.
At Siemens Energy, we are more than just an energy technology company. With +100,000 dedicated employees in more than 90 countries, we develop the energy systems of the future, ensuring that the growing energy demand of the global community is met reliably and sustainably. The technologies created in our research departments and factories drive the energy transition and provide the base for one sixth of the world’s electricity generation.
Our global team is committed to making sustainable, reliable, and affordable energy a reality by pushing the boundaries of what is possible. We uphold a 150-year legacy of innovation that encourages our search for people who will support our focus on decarbonization, new technologies, and energy transformation.
Find out how you can make a difference at Siemens Energy: [1] https://www.siemens-energy.com/employeevideo
Lucky for us, we are not all the same. Through diversity, we generate power. We run on inclusion, and our combined creative energy is fueled by over 130 nationalities. Siemens Energy celebrates character-no matter what ethnic background, gender, age, religion, identity, or disability. We energize society, all of society, and we do not discriminate based on our differences.
- Flexible and hybrid working environment
- Opportunities for continuous professional and personal development
- Collaborative and inclusive international work environment
- Access to learning, training, and knowledge-sharing opportunities
- Competitive local benefits
- Opportunities to work with innovative technologies and contribute to impactful projects
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