About the role

Context Engineer at CapIntel responsible for integrating LLMs into the core platform with a focus on reliability. Collaborating with various teams to enhance advisor and client experience.

Responsibilities

Design and implement LLM-powered features into our core application via model APIs (e.g. Anthropic, OpenAI, Cohere), with a focus on reliability and production-readiness
Architect and maintain retrieval-augmented generation (RAG) pipelines, connecting language models to internal knowledge bases, databases, and live data sources
Manage context window strategy, determining what information enters the model, when, in what format, and at what level of compression to optimise for accuracy, cost, and latency
Design and implement agentic workflows enabling the platform to handle multi-step, autonomous tasks
Build guardrail and output validation layers that constrain model behaviour and ensure AI features act within well-defined, compliant boundaries
Develop reusable agent primitives, prompt templates, and workflow components that other engineers can build on independently
Build evaluation frameworks to measure context effectiveness, output quality, and agent reliability in production
Monitor deployed AI systems for failure patterns and implement mitigation strategies, feeding learnings back into continuous improvement cycles
Collaborate with Product, Product Engineering, Implementation, and Data teams to translate business requirements, and proof of concepts into production AI system specifications
Act as an internal practitioner and resource helping upskill the broader engineering team on context engineering principles and agentic best practices

5+ years of professional software engineering experience, with at least 1–2 years working with LLMs in a production context
Strong experience with Python or Node and building API-integrated backend services
Hands-on experience with an orchestration or execution framework
Working knowledge of RAG architecture, vector databases (e.g. Pinecone, pgVector, AWS OpenSearch), and semantic search
Familiarity with context management techniques: summarisation, chunking, session splitting, and memory strategies
Experience building or consuming REST APIs and integrating with third-party services
Comfortable collaborating with cross-functional teams in a fast-paced, high-growth environment
Strong problem-solving instincts and a willingness to learn and adapt as the field evolves.