Noah AI
Direct message the job poster from Noah AI
At Noah AI (still in stealth) , we’re building the next generation of autonomy — an AI agent that doesn’t just assist, but executes. From scheduling to email to travel, Noah handles the work that keeps humans from doing their best work. We believe every executive — and eventually, every professional — will have an assistant like Noah that anticipates their needs, remembers their context, and works seamlessly across Slack, SMS, voice, and email.
We’re tackling one of the hardest autonomous problems in AI: real‑world autonomy — combining reasoning, memory, and human‑in‑the‑loop precision to deliver magical reliability.
If you’re an engineer who dreams about pushing LLMs beyond chat into action, come build Noah with us in Palo Alto, CA.
We’re still early, but the mission is massive: to make
one billion people radically more productive.
Our first agent is ready at www.heynoah.io.
Founder : Ashish Toshniwal is a serial entrepreneur and product visionary who believes AI can give every professional their own “second self.” He previously founded
Y Media Labs (YML) , which he bootstrapped into a
600-person digital product agency valued at $350M.
You can learn about him here - https://www.ashishtoshniwal.com/
About the Role We’re looking for a hands‑on senior engineer to help build the next generation of agentic AI systems — deeply integrated, multimodal, context‑aware agents capable of reasoning, executing tasks, and scaling across real‑world workloads. You’ll own core backend systems that connect AI models with users, memory, and data — powering agents that feel both intelligent and human. This role blends backend engineering, AI application design, and systems thinking.
You’ll work closely with product and research teams to bring applied AI ideas into production, focusing on robustness, observability, and performance at scale.
Responsibilities
Architect and build scalable agentic frameworks: orchestration layers, memory systems, context pipelines, and multimodal inference services.
Design and maintain real‑time infrastructure using sockets, WebSockets, queues, and event streams.
Implement secure, fault‑tolerant APIs that serve as the foundation for AI‑driven assistants.
Integrate AI models and tools (LLMs, vision, audio, embeddings) with robust backend systems.
Contribute to prompt engineering, evaluation, and context optimization to ensure high‑quality model outputs.
Define and measure eval pipelines (behavioral, functional, and regression testing) to validate agent reliability.
Collaborate on data storage and retrieval strategies across SQL, NoSQL, and vector databases.
Optimize cloud infrastructure for cost, latency, and reliability (Google Cloud preferred, but not required).
Champion best practices for security, authentication, and access control in distributed AI systems.
Qualifications
5+ years in backend or distributed systems.
Required Skills
Strong background in backend or distributed systems (Python, Go, or similar).
Experience with WebSockets / real‑time messaging architectures.
Deep understanding of scaling systems and debugging production performance issues.
Working knowledge of cloud platforms (GCP, AWS, or Azure).
Solid grasp of authentication, authorization, and secure API design.
Familiarity with prompt engineering, evals, and context pipelines for AI applications.
Comfort with SQL and NoSQL storage systems.
Understanding of multimodal AI systems (language, vision, audio, or embeddings).
Strong debugging, observability, and structured logging habits.
Nice-to-Haves
Experience with agent frameworks (LangGraph, Semantic Kernel, CrewAI, etc.).
Background in machine learning or model inference optimization.
Experience integrating retrieval‑augmented generation (RAG) or memory systems.
Knowledge of structured evaluations for AI systems (model QA, test harnesses).
Familiarity with GCP services (Pub/Sub, Cloud Run, Cloud SQL, Artifact Registry, etc.).
Seniority level
Mid‑Senior level
Employment type
Full‑time
Job function
Information Technology
Industries
Technology, Information and Internet
#J-18808-Ljbffr
At Noah AI (still in stealth) , we’re building the next generation of autonomy — an AI agent that doesn’t just assist, but executes. From scheduling to email to travel, Noah handles the work that keeps humans from doing their best work. We believe every executive — and eventually, every professional — will have an assistant like Noah that anticipates their needs, remembers their context, and works seamlessly across Slack, SMS, voice, and email.
We’re tackling one of the hardest autonomous problems in AI: real‑world autonomy — combining reasoning, memory, and human‑in‑the‑loop precision to deliver magical reliability.
If you’re an engineer who dreams about pushing LLMs beyond chat into action, come build Noah with us in Palo Alto, CA.
We’re still early, but the mission is massive: to make
one billion people radically more productive.
Our first agent is ready at www.heynoah.io.
Founder : Ashish Toshniwal is a serial entrepreneur and product visionary who believes AI can give every professional their own “second self.” He previously founded
Y Media Labs (YML) , which he bootstrapped into a
600-person digital product agency valued at $350M.
You can learn about him here - https://www.ashishtoshniwal.com/
About the Role We’re looking for a hands‑on senior engineer to help build the next generation of agentic AI systems — deeply integrated, multimodal, context‑aware agents capable of reasoning, executing tasks, and scaling across real‑world workloads. You’ll own core backend systems that connect AI models with users, memory, and data — powering agents that feel both intelligent and human. This role blends backend engineering, AI application design, and systems thinking.
You’ll work closely with product and research teams to bring applied AI ideas into production, focusing on robustness, observability, and performance at scale.
Responsibilities
Architect and build scalable agentic frameworks: orchestration layers, memory systems, context pipelines, and multimodal inference services.
Design and maintain real‑time infrastructure using sockets, WebSockets, queues, and event streams.
Implement secure, fault‑tolerant APIs that serve as the foundation for AI‑driven assistants.
Integrate AI models and tools (LLMs, vision, audio, embeddings) with robust backend systems.
Contribute to prompt engineering, evaluation, and context optimization to ensure high‑quality model outputs.
Define and measure eval pipelines (behavioral, functional, and regression testing) to validate agent reliability.
Collaborate on data storage and retrieval strategies across SQL, NoSQL, and vector databases.
Optimize cloud infrastructure for cost, latency, and reliability (Google Cloud preferred, but not required).
Champion best practices for security, authentication, and access control in distributed AI systems.
Qualifications
5+ years in backend or distributed systems.
Required Skills
Strong background in backend or distributed systems (Python, Go, or similar).
Experience with WebSockets / real‑time messaging architectures.
Deep understanding of scaling systems and debugging production performance issues.
Working knowledge of cloud platforms (GCP, AWS, or Azure).
Solid grasp of authentication, authorization, and secure API design.
Familiarity with prompt engineering, evals, and context pipelines for AI applications.
Comfort with SQL and NoSQL storage systems.
Understanding of multimodal AI systems (language, vision, audio, or embeddings).
Strong debugging, observability, and structured logging habits.
Nice-to-Haves
Experience with agent frameworks (LangGraph, Semantic Kernel, CrewAI, etc.).
Background in machine learning or model inference optimization.
Experience integrating retrieval‑augmented generation (RAG) or memory systems.
Knowledge of structured evaluations for AI systems (model QA, test harnesses).
Familiarity with GCP services (Pub/Sub, Cloud Run, Cloud SQL, Artifact Registry, etc.).
Seniority level
Mid‑Senior level
Employment type
Full‑time
Job function
Information Technology
Industries
Technology, Information and Internet
#J-18808-Ljbffr