AI Engineer

Job Description

Advanced Analytics Full Time TORONTO, ON Hybrid

Dig Insights is a tech-enabled research company that helps our clients - global consumer brands - move beyond consumer‑centric to decision‑centric. Our clients can then go‑to‑market with innovations that shift consumer decisions in their favor.

Our work is supported by the technologies that we leverage and create. This includes Upsiide, our proprietary innovation insights platform. Upsiide is a SaaS platform that reinvents how enterprise companies screen, optimize, and build a business case for innovation.

Our clients span verticals including CPG, QSR, retail, technology, financial services, and telecommunications. Our work is led by a team of over 250 strategists, insights leaders and data scientists. We work for a global client base out of offices in Toronto, Chicago, and London.

Our success is due to our strong commitment to our clients, and the creativity and dedication of our entire team. Since the beginning, we have been focused on building the smartest consumer insights company and that means hiring people who are bright, creative, resourceful, and kind. People who succeed at Dig are curious, question established norms and are passionate about helping our clients to move their businesses forward. If you want to join a team that takes themselves just seriously enough to produce great work, we’d love to welcome you.

As we continue to grow, both geographically and in our expertise we are looking for people who want to join a high‑growth and highly collaborative company.

AI Engineer – About this role

Dig Insights is seeking an AI Engineer to build, deploy, and scale AI‑driven features and services across the market research process, with a focus on our internal research platform. You will work across API development, LLM agents, MCP server implementation, and RAG workflows, collaborating closely with engineering, product, and research teams to productionize high‑impact, reliable AI capabilities.

Your primary responsibilities will include, but are not limited to:

Developing and Deploying APIs and MCP Tools

• Develop and maintain APIs that deliver AI‑powered features across Dig Insights products.


• Optimize performance, latency, and cost across multiple model providers.


• Build and maintain MCP (Model Context Protocol) tools, including tool/resource definitions, protocol‑compliant communication, and integration with internal systems.


• Ensure reliability through strong observability, testing, and monitoring.

LLM Pipelines and Retrieval

• Build LLM pipelines including prompt engineering, embeddings, retrieval‑augmented generation (RAG), and evaluation.


• Implement and refine vector search and semantic retrieval components.


• Develop modular components that support experimentation with new LLMs, APIs, and prompting strategies.


• Support robust ingestion and transformation of data for retrieval workflows and context building, ensuring proficiency in cleaning, structuring, and optimizing data as it moves through LLM pipelines.


• Configure and optimize vector databases to support scalable semantic search.

Continuous Learning, Improvement, and Benchmarking

• Stay current with relevant new models, APIs, frameworks, and orchestration tooling. Track advancements in AI engineering, retrieval techniques, and MCP standards.


• Benchmark models, embeddings, and retrieval strategies to guide technical decisions and recommend improvements to development workflows, pipelines, and architectural patterns.


• Experiment with emerging models and techniques, and evaluate their applicability to Dig Insights products.

Collaboration and Documentation

• Work with product, engineering, and research teams to design and deploy AI‑powered features.


• Produce clear documentation for LLM pipelines, API interfaces, MCP implementations, and architectural decisions.


• Share best practices and support junior contributors when needed.

Education

Bachelor's or Master’s in Computer Science, Engineering, Machine Learning, Data Science, or a related field.

Experience

2+ years engineering LLM‑based or AI‑driven applications in production environments.

Technical Skills

• Strong Python proficiency, machine learning fundamentals (e.g., model evaluation and metrics), and experience with modern LLM ecosystems (OpenAI, Anthropic, Hugging Face, etc.).


• Experience developing and maintaining high‑performance APIs (e.g., FastAPI, Flask).


• Experience building agentic AI systems and integrating MCP servers with structured tools and resources.


• Familiarity with vector databases, embeddings, and retrieval pipelines powering RAG systems (e.g., Elasticsearch, Pinecone, pgvector).


• Understanding of data engineering fundamentals relevant to LLM workflows.


• Experience with AWS cloud services (including Lambda, Batch, CloudWatch, and API Gateway) or other cloud platforms, as well as serverless development, Docker, and observability/test automation tools.


• Experience integrating AI components into production software systems.


• WebSocket experience is a plus.

Soft Skills

• Strong communication and problem‑solving abilities.


• Curious, detail‑oriented, and able to learn rapidly in a fast‑moving technical landscape.


• Comfortable working independently and collaboratively.

Why Join Us?

• Flexible hybrid work environment.


• Build impactful, production‑ready AI features used across Dig Insights products.


• Work with a team pushing the boundaries of applied LLM engineering and insights technology.


• Hybrid working policy which gives the flexibility to employees to work remotely or in one of our office locations.


• Unlimited vacation policy.


• Reimbursement for health and wellness classes/memberships, and continuous learning.


• Medical Insurance.


• In‑person and virtual social events such as poker night, paint night, trivia night and more!

Our culture is built on 5 core values: Energy, Excellence, Evolution, Equality and Empathy. We believe that our success is dependent on the diverse talents, skills, and ideas of its staff. We are committed to creating an inclusive work environment and encourage applications from all qualified candidates including those in the BIPOC and LGBTQ communities, and from people with disabilities.

We thank you for your interest in Dig Insights, however, only candidates who are chosen for an interview will be contacted.