AI Architect

Software AG•Reston, VA

1d•Remote

About The Position

Software AG is seeking a highly experienced Artificial Intelligence (AI) architect to spearhead the integration of cutting-edge AI technologies into our product portfolio. This role involves unlocking new values for customers across diverse sectors by leveraging AI for software development, IT operations, data integration, virtual assistants and agents, and AI-driven modernization. The AI Architect will lead AI innovation, identify use cases, contribute to product roadmaps, and collaborate with customers to understand their business objectives and translate them into actionable features. The role also involves designing and architecting robust and scalable AI products, building prototypes, staying aware of competitive and market trends in AI and data integration, and collaborating with product management, engineering, and solution architects. Additionally, the AI Architect will act as a thought leader, presenting at conferences and webinars, and continuously educating internal teams on AI technologies and best practices.

Requirements

Minimum of 8 years in software architecture, data integration, or solution engineering.
At least 2 years of hands-on work with generative AI in production or customer-facing projects.
Bachelor's degree in Computer Science, Information Systems, Software, Electrical or Electronics Engineering, or comparable field of study, and/or equivalent work experience.
Proven hands-on experience with LLMs and agentic AI: context engineering, tool calling, RAG-based architecture, agent frameworks, MCP and A2A protocols, and MLOps practices.
Strong programming skills in Python or Typescript.
Experience with AI frameworks and tools (e.g., PyTorch, Langchain, LlamaIndex, Transformers, ONNX).
Solid understanding of enterprise data access: SQL, ODBC/JDBC, REST APIs, and data security concepts such as access control and data masking.
Experience with at least one major cloud AI platform (Azure OpenAI, AWS Bedrock, Google Vertex) and with running models on premises.
Proficiency in Linux, virtualization, version control, and containerization technologies.
Excellent problem-solving skills, with a keen ability to troubleshoot and solve complex tasks.
Effective communication and presentation skills (verbal, written) in English to convey technical concepts and solutions to both technical and non-technical stakeholders.
Customer-focused mindset: Proven ability to collaborate effectively with customers and partners, understanding their needs and providing tailored solutions.
Collaborative team player and experience in enabling and mentoring stakeholders.
Ability to work in a highly agile environment with globally distributed teams.
Self-learning and self-driving attitude delivering results according to goals and measurements.
Proven ability to collaborate with R&D to drive success.
Strong organizational and time-management skills to effectively manage multiple tasks and deadlines.
Self-learning and self-driving attitude delivering results.
Occasional international travel is required (less than 20%).

Nice To Haves

Advanced degrees such as Masters or PhD is preferred.
Knowledge of Adabas, Natural, or CONNX.
Experience with mainframe or non-relational data: VSAM, IMS, COBOL copybooks, hierarchical structures.
Experience building evaluation pipelines or benchmarks for AI output.
Experience with fine-tuning open-weight AI models.

Responsibilities

Lead AI Innovation: Identify compelling AI use cases, contributing directly to product innovation and roadmap definition within our Adabas & Natural, CONNX and JOPAZ ecosystem.
Customer Collaboration: Work closely with customers to deeply understand their business objectives, identify AI opportunities, address their unique challenges, and translate them into actionable features for our product roadmap.
Solution Design & Architecture: Propose innovative, robust and scalable AI products and capabilities, collaborating with key AI technology partners to jointly design and implement integrated solutions.
Prototypes and MVPs: Design, build, and evaluate prototypes that show real value with real customer data.
Competitive and Market Awareness: Follow competitors, and open-source projects in AI, data integration, and mainframe modernization. Represent Software AG in relevant industry bodies and standards groups when needed.
Cross-Functional Collaboration: Work closely with product management, engineering, and solution architects to drive, coordinate and deliver AI capabilities.
Thought Leadership: Present at internal and external conferences, webinars, and in written content. Explain complex topics in a way that both technical and business audiences understand.
Continuous Learning & Team Enablement: Keep pace with fast-moving AI technologies and trends, and continuously educate and upskill internal teams - product management, engineering, consulting, and support - through training sessions, hands-on workshops, and shared best practices.