Principal AI Systems Architect

About the Position

Principal AI Systems Architect

Braşov, Romania

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About the Role

This is the person who builds that architecture. As Principal AI Systems Architect you own Mimoid's long-term technical architecture and drive it from today's shipping product to the full platform vision. You will design and stand up the shipbuilding-native stack the company compounds on, and you will be hands-on - containerizing services, deploying into the cloud, and prototyping the hard parts, not just drawing diagrams. You work directly with the CEO and CTO and set the standards the rest of engineering builds against.

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Responsibilities

• Own the end-to-end target architecture and the phased roadmap to reach it - evolving the Phase-1 modular monolith (FastAPI API + Celery worker, managed data) into service-ready boundaries that extract into microservices and a service mesh only when a named trigger forces it.
• Architect and operate the cloud + deployment foundation: containerize services, run them in the cloud, and design per-project isolation as a hard gate. Own CI/CD, secrets/encryption, observability, and cost-per-build instrumentation.
• Design the knowledge-graph core: a property-graph database (e.g., Neo4j) paired with a relational + vector store (PostgreSQL/pgvector) for hybrid retrieval, bi-temporal and change-impact edges, provenance on every value, and the domain ontology - plus the context service that grounds and token-budgets every agent call.
• Architect the agent runtime - orchestration, tool calling, human-in-the-loop gates, and trace/replay/cost telemetry - and a versioned, eval-gated prompt registry.
• Own the model-serving abstraction: route every call by classification and complexity across a tiered set of managed models (small medium large), CPU-servable local embeddings, a deterministic mock provider for CI, and a local open-weight + LoRA fallback.
• Design the continuous-learning plane: capture evaluate (eval harness, calibration, trust tiers) curate adapt (LoRA / rule update) promote (shadow canary production with auto-rollback), plus an anonymized, consent-gated, privacy-preserving cross-site learning network.
• Keep the numeric decision path deterministic and auditable - scheduling (critical-path methods) and flow optimization (constraint solvers such as OR-Tools CP-SAT) run with no LLM in the loop.
• Write the ADRs and reference architecture; make build-vs-buy, open-weight-vs-proprietary, and coupling decisions; own FinOps for LLM and compute spend.

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Requirements

• 10+ years in software/systems engineering, including 4+ years owning production system architecture end-to-end.
• Cloud & deployment (hands-on): deep experience on a major cloud platform - containerization (Docker), container runtime/orchestration, infrastructure-as-code, CI/CD, and running managed data services (PostgreSQL, object storage, Redis) in production. You can stand the system up yourself, not just specify it.
• Knowledge graph: hands-on graph experience - Neo4j (or a comparable property-graph engine), property-graph/ontology modeling, and graph-backed retrieval; comfort pairing a graph with a vector store (pgvector or equivalent) for hybrid retrieval.
• AI / agents: architecting LLM and multi-agent systems - RAG, embeddings/reranking, agent runtimes and tool-calling, prompt/version registries, evals, and LLMOps/observability.
• Model serving: experience routing across models/providers and reasoning about cost/latency/quality tradeoffs.
• Data & correctness: relational + vector data modeling, provenance/lineage, and keeping deterministic compute separate from probabilistic components.
• Fluency architecting polyglot systems (Python/FastAPI + TypeScript/Node) and writing clear ADRs and reference architectures.

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Preferred Qualifications

• Experience taking an early-stage platform to a compliant, multi-tenant production posture (e.g., SOC 2, ISO 27001).
• Hands-on with private, on-premise, or air-gapped inference environments.
• Local/open-weight model fine-tuning (LoRA) and evaluation-gated model promotion.
• Operations-research / optimization exposure (CP-SAT, critical-path scheduling).
• Domain background in PLM/PDM/BOM systems or complex high-mix, low-volume manufacturing

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We Offer

• Competitive salary
• Opportunity to work in a cutting-edge field of AI systems architecture
• Collaborative environment with direct access to the CEO and CTO
• Professional growth and development opportunities

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About the Company

Mimoid is a forward-thinking company dedicated to revolutionizing the way we design and build complex systems. We are committed to pushing the boundaries of technology and innovation, and we are looking for passionate and skilled individuals to join our team.