Principal / Distinguished Engineer - Distributed Systems, Graph Databases, and Planet-Scale AI [...]

Anonymous; Laguna Beach (CA); On-site; USD 180,000 - 250,000; Full time

Job summary

A leading technology firm is seeking a Principal / Distinguished Engineer to architect and scale distributed systems for AI. The role involves designing microservices architectures and mentoring senior engineers. Candidates should have extensive experience in distributed systems and programming proficiency in languages like Go, Rust, and Python. Join to shape the future of lawful intelligence and AI collaboration.

Qualifications

• 12–18 years of experience designing and scaling distributed systems.
• Recognized as a Principal, Distinguished, or Chief Engineer.
• Deep proficiency in multiple programming languages.
• History of end-to-end ownership of scalable systems.

Responsibilities

• Architect and build the distributed computing backbone for AI.
• Design microservices architecture for low-latency workloads.
• Mentor senior engineers and establish DevSecOps standards.
• Collaborate with AI research teams for production deployment.

Skills

Distributed Systems

Microservices

Graph Databases

AI Integration

Data Integrity

Programming Languages (Go, Rust, C++, Scala/Java, Python)

Education

Master’s or PhD in Computer Science, Electrical Engineering, or Applied Mathematics

Tools

Kafka

Pulsar

Flink

Job description

Principal / Distinguished Engineer - Distributed Systems, Graph Databases, and Planet-Scale AI Infrastructure

Mobius is creating the foundational infrastructure for the next generation of AI economies—systems where intelligence, data, and capital interoperate through verifiable, lawful computation.

We’re seeking a hands‑on Distinguished Engineer to architect, build, and scale the distributed computing backbone that supports real‑time, AI‑driven decisioning and neuro‑symbolic reasoning at planetary scale. You will lead architecture for microservices, graph databases, and distributed computation, building the substrate upon which AI ecosystems, autonomous agents, and digital marketplaces operate.

Responsibilities

• Design and evolve a planet‑scale microservices fabric supporting low‑latency, high‑consistency workloads across multi‑cloud and sovereign infrastructures.
• Define the knowledge and event graph architecture integrating structured, semi‑structured, and streaming data for real‑time AI reasoning.
• Develop architectural patterns that enable autonomous AI systems to collaborate and self‑orchestrate safely.
• Implement global replication, partitioning, and failover strategies balancing CAP, PACELC, and ethical‑compliance constraints.
• Engineer scalable, low‑latency graph and vector databases optimized for AI reasoning and contextual retrieval.
• Build real‑time pipelines that fuse symbolic and statistical models—neuro‑symbolic AI—into continuously learning, explainable systems.
• Architect hybrid transactional‑analytical (HTAP) layers for streaming inference and knowledge updating.
• Embed observability, lineage, and auditability into every data flow to support transparent and trustworthy AI operation.

Scalability, Performance, and Reliability

• Create self‑healing, auto‑scaling distributed systems capable of 24×7 uptime across continents.
• Use consensus protocols (RAFT, CRDTs, Paxos, vector clocks) and streaming frameworks (Kafka, Pulsar, Flink) to maintain data integrity at exabyte scale.
• Lead performance tuning, resource optimization, and telemetry‑driven capacity planning for compute‑ and data‑intensive AI workloads.

Engineering Leadership

• Mentor senior engineers across infrastructure, data systems, and AI integration.
• Establish gold standards for DevSecOps automation, infrastructure‑as‑code, and continuous deployment across hundreds of interdependent services.
• Collaborate with AI research teams to translate algorithmic prototypes into robust, distributed production environments.

Candidate Pedigree

• 12–18 years of experience designing and scaling distributed systems in top‑tier technology organizations (cloud hyperscalers, leading AI labs, or equivalent).
• Recognized as a Principal, Distinguished, or Chief Engineer with architectural ownership of global‑scale systems or data platforms.
• Advanced degree (Master’s or PhD) in Computer Science, Electrical Engineering, or Applied Mathematics from a leading institution.
• Deep proficiency in multiple languages (Go, Rust, C++, Scala/Java, Python) and familiarity with modern distributed frameworks.
• Demonstrated contributions to open‑source, patents, or published research in distributed databases, graph reasoning, or AI infrastructure.
• Exceptional ability to bridge systems engineering, data science, and product strategy in service of next‑generation AI economies.
• Operate comfortably at the intersection of AI research, distributed systems, and product design.
• Demonstrated history of end‑to‑end ownership—from whiteboard architecture to deployed, scaled, and monitored systems.
• Strong communication skills, ability to influence senior leadership, and passion for mentoring other architects.
• Commitment to building technology that advances both capability and integrity in the emerging AI‑driven economy.

Why Join

This is an opportunity to architect the computational backbone of lawful intelligence—software that will underpin global‑scale AI collaboration, digital governance, and the economy of the 21st century. You will work at the confluence of distributed systems, advanced databases, and AI research, shaping how humanity and intelligent systems share information and value.

Seniority level

Mid‑Senior level

Employment type

Full‑time

Job function

Engineering and Information Technology