Staff Engineer: Context & Memory for Agentic AI

United States Digital Space LLC; Greater London; On-site; GBP 120,000 - 180,000; Full time

Job summary

Scale is seeking a Staff Software Engineer in London to own end-to-end context and memory systems for agentic AI platforms. You will design and optimize backend systems, retrieval, and memory strategies, while guiding evaluation methods and technical standards.

Collaboration with SWE and ML teams is essential to ensure reliability at scale. You will work across memory, retrieval, and evaluation, balancing software engineering with applied ML expertise, and contributing to production-grade agent

Qualifications

• 8+ years of engineering experience, with a multi-year track record owning production systems end to end.
• Experience with ML and information retrieval problems in modern AI systems, including embeddings, vector search, retrieval augmented generation, fine-tuning, or memory architectures.
• Proficiency in Python and infrastructure for production ML/agentic systems (containers, cloud platforms, CI/CD).
• Ability to set technical standards and influence decisions beyond own team through design reviews or mentoring.

Responsibilities

• Own large, ambiguous problems in context and memory end to end, from design to production.
• Architect core primitives for context retrieval, storage, and reasoning across long-running sessions.
• Design and maintain evaluation methodologies for memory and retrieval quality.
• Set technical standards and patterns adopted by the team, including failure handling.
• Collaborate with SWE and ML engineering peers along the roadmap across multiple workstreams.
• Debug and resolve severe production issues related to context and memory, including cross-tenant leakage.

Skills

Python

Distributed systems

ML systems

Information retrieval

Vector search

Embeddings

Cloud platforms

CI/CD

Tools

Containers

Vector stores

Big data tooling

Job description

Scale is seeking a Staff Software Engineer in London to own end-to-end context and memory systems for agentic AI platforms. You will design and optimize backend systems, retrieval, and memory strategies, while guiding evaluation methods and technical standards.

Collaboration with SWE and ML teams is essential to ensure reliability at scale. You will work across memory, retrieval, and evaluation, balancing software engineering with applied ML expertise, and contributing to production-grade agent