Production LLM Context Engineer

CapIntel Inc.; Ottawa; Hybrid; CAD 120,000 - 150,000; Full time

Job summary

CapIntel is seeking a Context Engineer to join our AI infrastructure team. You will design and implement LLM-powered features in our core application, focusing on reliability, production-readiness, and seamless integration with internal data sources.

You will work with engineers, product managers, and domain experts to build reusable components, guardrails, and evaluation frameworks, helping CapIntel deliver trusted AI capabilities that enhance advisor and client experiences.

Qualifications

• 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, 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.

Responsibilities

• Design and implement LLM-powered features into our core application via model APIs, 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 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

Skills

Python

Node.js

API design

LLMs in prod

RAG pipelines

REST APIs

Tools

Docker

Kubernetes

Pinecone

pgVector

AWS OpenSearch

LangSmith

Job description

CapIntel is seeking a Context Engineer to join our AI infrastructure team. You will design and implement LLM-powered features in our core application, focusing on reliability, production-readiness, and seamless integration with internal data sources.

You will work with engineers, product managers, and domain experts to build reusable components, guardrails, and evaluation frameworks, helping CapIntel deliver trusted AI capabilities that enhance advisor and client experiences.