Engineering12+ yearsFull-time
Principal Software Architect
We are seeking a highly experienced Principal Software Architect to architect and technically lead the development of a sophisticated AI-enabled enterprise platform designed for large global organizations. This is a hands-on role spanning enterprise architecture, generative AI, LLMs, semantic and enterprise data modeling, knowledge graphs, security, governance, and distributed systems. The platform integrates and reasons across complex structured and unstructured enterprise data, with exceptionally high standards for accuracy, security, explainability, traceability, compliance, scalability, and reliability.
Responsibilities
- Own the end-to-end enterprise, application, data, integration, AI, security, and cloud architecture.
- Design enterprise canonical data models, semantic models, ontologies, knowledge graphs, entity relationships, provenance, lineage, and cross-system identity resolution.
- Architect AI solutions using LLMs, generative AI, RAG, GraphRAG, semantic search, embeddings, vector databases, knowledge graphs, and agentic workflows.
- Define strategies for LLM fine-tuning, domain adaptation, model selection and routing, prompt engineering, grounding, confidence scoring, and hallucination mitigation.
- Design AI evaluation frameworks covering accuracy, precision and recall, explainability, evidence attribution, and model performance.
- Design hybrid intelligence combining deterministic rules, enterprise data, graph traversal, retrieval, LLM reasoning, and human validation.
- Architect integrations with PLM, ERP, MES, QMS, ALM, document management, and other enterprise systems.
- Design scalable distributed, event-driven, workflow and state-machine, synchronization, reconciliation, and audit architectures.
- Establish enterprise-grade SSO, RBAC/ABAC, encryption, data isolation, AI security, governance, and compliance controls.
- Lead technical R&D, proof-of-concepts, Architecture Decision Records (ADRs), architecture and code reviews, and engineering implementation.
Requirements
- 12+ years in software engineering with significant Principal or Lead Architect experience.
- Proven experience designing and delivering complex enterprise-scale platforms.
- Strong expertise in enterprise architecture, data architecture, semantic modeling, distributed systems, APIs, event-driven architecture, and enterprise integrations.
- Hands-on experience with generative AI, LLMs, RAG and GraphRAG, embeddings, semantic search, knowledge graphs, vector databases, and LLM evaluation and fine-tuning or domain adaptation.
- Strong understanding of enterprise security, identity, data governance, auditability, high availability, observability, and cloud architecture.
- Experience with AWS, Azure, and/or GCP.
Nice to have
- Experience with SAP, Siemens Teamcenter, PTC Windchill, or Oracle.
- Experience in PLM, ERP, or manufacturing environments.
- Experience with Kafka, graph databases, workflow engines, and Kubernetes.
- Familiarity with standards such as ISO 27001, SOC 2, or NIST.
What we value
- A hands-on deep-tech architect, not an architecture-diagram-only role.
- Able to move from architecture into data models, APIs, event contracts, AI pipelines, security models, PoCs, reference implementations, code reviews, and production engineering.
- Understands that reliable enterprise AI requires more than an LLM — it needs the correct combination of semantic models, enterprise data, knowledge graphs, deterministic controls, retrieval, AI reasoning, security, human governance, and measurable evaluation.
- Treats accuracy, security, data integrity, explainability, governance, and engineering quality as fundamental.
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