Position Title: AI Engineer (Agentic Workflows) Department: Research & Development In-Office Employment Type: Full-Time Shift: Dayshift Level: Mid–Senior (Expected Experience: 3+ Years) After all, we spend at least a third of our lives working—so why not create workplaces where people want to come to work in the morning and feel good when they leave at the end of the day? Does this sound like something you'd want to be a part of and help grow? Protocase specializes in custom sheet metal enclosures, panels, and parts for engineers and innovators worldwide, built with unmatched speed and quality.

As an AI Engineer (Agentic Workflows) at Protocase, you will design and build applications, automations, and agentic systems on top of existing large language models (LLMs) and foundation models. You'll think in terms of workflows and outcomes—identifying where an agentic or AI-assisted process can replace or augment manual work—and move from abstract problem statements to concrete, working pipelines. This role does not require deep expertise in training or fine-tuning models from scratch.

It requires strong software engineering fundamentals, systems thinking, and fluency in the current landscape of LLM APIs, agent frameworks, and retrieval tooling. Integrate large language models into products and internal tools via APIs and open-source inference/serving frameworks. Architect retrieval-augmented generation (RAG) pipelines, including document ingestion, chunking strategy, embedding selection, and vector database integration.

Build evaluation harnesses and test suites to measure agent and workflow accuracy, reliability, and regression over time. Translate ambiguous, high-level business problems into scoped technical specifications and working prototypes. Monitor deployed AI workflows in production, using observability tooling to track latency, cost, and output quality.

Stay current with the fast-moving AI agent and tooling ecosystem and recommend adoption of new frameworks, models, or techniques where warranted. Bachelor's degree in Computer Science, Software Engineering,



or equivalent practical experience. 3+ years of professional software development experience. ~ Demonstrated experience building applications on top of LLM APIs, including API providers or self-hosted inference. ~ Technical Skills Solid understanding of RAG architecture: embeddings, vector search, chunking, and retrieval strategy. Strong general-purpose programming ability in Python and/or a modern backend language.

Ability to reason abstractly about a business problem and independently design a technical approach to solve it. Ability to work in-office in Sydney, Nova Scotia.

What Would Be

Considered an Asset (Nice-to-Have Qualifications) The following qualifications are not required, but would be considered an asset.

Experience with vector databases and hybrid search/reranking techniques. Familiarity with LLM inference/serving frameworks and gateway/proxy layers for model routing.

Experience building or maintaining evaluation and observability pipelines for AI systems.Prior experience scoping and delivering AI features or automations in a production environment. Basic familiarity with model fine-tuning concepts, even without hands-on training experience. You're a strong software engineer who sees AI as a systems problem, not just a prompting problem.

You enjoy taking an ambiguous business challenge, breaking it down into something concrete, and building a practical solution that works reliably in the real world. Enjoy turning loosely defined problems into well-scoped technical solutions. Are comfortable building with LLM APIs, retrieval systems, orchestration frameworks, and external tools.

Know that a successful AI application requires more than a good prompt—it needs thoughtful architecture, evaluation,



monitoring, and iteration. Can move quickly from experimentation and prototyping to reliable, production-ready software. Are curious about emerging AI capabilities without automatically chasing every current framework or model.

Make pragmatic technical decisions based on the problem, rather than forcing a preferred tool or architecture. Enjoy working directly with stakeholders to understand how work gets done and where AI can meaningfully improve it. Take ownership of the systems you build, including their reliability, cost, performance, and long‐term maintainability.

Communicate technical concepts clearly with both engineering and non-technical teams. Want to help shape how AI and agentic systems are used across a growing organization. You're interested in building AI systems that solve real problems, hold up outside of a demo, and create measurable value for the people who use them.

Our starting annual total compensation package—including base salary and performance incentives—ranges from $69,775 to $120,000 CAD, depending on experience.

Training & Growth: Leadership training, skills development opportunities, regular coaching, and clear pathways for career growth.

Comprehensive Health Care Plan & Company RRSP: Medical, Dental, Life Insurance, Group Insurance, and a Company RRSP after six months of full-time employment.

Vacation: Start with two weeks of paid vacation, increasing to three weeks after three years and four weeks after five years.

Community Discounts: Access exclusive discounts at local businesses and restaurants. Enjoy a cost-shared YMCA membership, wellness initiatives, and access to a pension plan after three months of employment.

Social Events: Regular social events, including seasonal parties, monthly lunches, and team celebrations. Lifestyle of Cape Breton, Nova Scotia: Live in a community with quick commutes, affordable homes on generous plots of land, beautiful scenery, and friendly people—a lifestyle that marries nature with a vibrant culture.

📌 AI Engineer (Agentic Workflows) (Sydney)
🏢 Aimlroles
📍 Sydney