What are the responsibilities and job description for the Senior AI Engineer position at Stealth Post-LLM Startup?
About Dyssonance
Dyssonance is reimagining how AI thinks. We are building the Large Thinking Model (LTM) to move beyond static pattern matching, creating systems capable of memory, dynamic reasoning, and evolving beliefs. Founded by leaders from DeepMind and Google, we are a small, elite team dedicated to solving foundational challenges in AI cognition.
We are assembling the scaffolding for a new AI paradigm. If you thrive where cutting-edge research meets massive infrastructure challenges, this is your moment.
About the Role
As a Senior AI Engineer at Dyssonance, you will architect and build the foundational infrastructure that powers our Large Thinking Models. This is not a standard backend role. You will be responsible for designing the high-throughput, low-latency distributed systems and the complex knowledge graph architecture required to manage the immense scale of evolving AI thought models.
You will ensure our infrastructure can support real-time reasoning and dynamic belief updating, enabling our research team to iterate at the speed of thought.
What You’ll Do:
- Design and implement the core distributed systems architecture that powers our LTMs, optimizing for performance, scalability, and resilience.
- Architect and manage large-scale knowledge graphs to represent the AI’s dynamic memory, relationships, and complex belief states.
- Build robust, scalable APIs and services for model inference, training pipelines, and research access.
- Collaborate directly with AI Researchers and ML Engineers to transition novel reasoning prototypes into production-ready systems.
- Own the infrastructure roadmap for data ingestion, storage, and retrieval in a complex, high-volume environment.
- Tackle hard problems in system reliability and observability as we scale our cognitive architectures.
What We’re Looking For:
- 5 years of experience in backend engineering, focusing on data-intensive, high-performance systems.
- Deep expertise in designing, building, and operating large-scale distributed systems (e.g., using Kubernetes, Ray, or custom architectures).
- Proven track record with graph databases (e.g., Neo4j, TigerGraph, Dgraph) and complex knowledge graph construction/traversal.
- Strong proficiency in Python; experience with high-performance languages (e.g., Go, Rust, or C ) is highly valued.
- Extensive experience with cloud infrastructure (AWS, GCP, or Azure) and modern DevOps practices (CI/CD, IaC).
- Familiarity with vector databases (e.g., Pinecone, Weaviate) and MLOps tooling is a significant plus.
- A bias for speed, rigor, and the ability to thrive in a fast-paced, research-driven environment.
Why Dyssonance
- Work with a founding team of ex–DeepMind and Google researchers and engineers.
- Shape the foundational infrastructure of a new class of AI systems — one that thinks, remembers, and reasons.
- Operate at the intersection of systems engineering, applied research, and moonshot-scale vision.
- Fully remote, globally distributed team with a culture of high ownership and intellectual courage.
To Apply: Send your CV, links to relevant code/projects, and a short note on the most interesting distributed systems challenge you’ve solved to jobs@dyssonance.ai.