Context Engineer

This is a fully remote position, open to applicants in Canada.

📋 Description

• Design and integrate LLM-driven functionalities into our primary application utilizing model APIs (e.g., Anthropic, OpenAI, Cohere), prioritizing reliability and production readiness.

• Architect and sustain retrieval-augmented generation (RAG) pipelines, linking language models to internal knowledge bases, databases, and real-time data sources.

• Oversee context window strategy, deciding what information is fed into the model, the timing, format, and level of compression to optimize for accuracy, cost, and latency.

• Design and implement agentic workflows that allow the platform to perform multi-step, autonomous tasks.

• Develop guardrails and output validation mechanisms to regulate model behavior and ensure AI features operate within clearly defined, compliant boundaries.

• Create reusable agent components, prompt templates, and workflow elements that other engineers can leverage independently.

• Establish evaluation frameworks to assess context effectiveness, output quality, and agent reliability in a production environment.

• Monitor deployed AI systems for failure patterns and execute mitigation strategies, incorporating insights into continuous improvement processes.

• Collaborate with Product, Product Engineering, Implementation, and Data teams to convert business requirements and proof of concepts into production AI system specifications.

• Serve as an internal expert and resource, aiding in the upskilling of the broader engineering team on context engineering principles and agentic best practices.

⛳️ Requirements

• Over 5 years of professional software engineering experience, including 1–2 years working with LLMs in a production setting.

• Extensive experience with Python or Node and developing API-integrated backend services.

• Practical experience with an orchestration or execution framework.

• Familiarity with RAG architecture, vector databases (e.g., Pinecone, pgVector, AWS OpenSearch), and semantic search.

• Knowledge of context management techniques: summarization, chunking, session splitting, and memory strategies.

• Experience in building or consuming REST APIs and integrating with third-party services.

• Ability to collaborate with cross-functional teams in a dynamic, high-growth environment.

• Strong problem-solving skills and a readiness to learn and adapt as the field progresses.

🏝️ Benefits

• Compensation that exceeds base pay (variable pay, equity).

• Comprehensive benefits package.

• Flexible time off policy.

• Opportunities for professional growth and development.