Hygiena provides rapid microbiology diagnostic tests and solutions for mission-critical, time-sensitive processes around the world. Hygiena’s proprietary diagnostic technologies enable customers to; prevent illness and save lives, comply with regulations, protect products and brands, run businesses more effectively. Solutions are sold in a wide range of industries globally, but the core focus is food safety.
Headquartered in Camarillo, California and with offices around the world, we are actively looking for talented individuals to help grow the business!
At Hygiena we believe:
- In providing the highest quality products & service
- Being a leader in innovation
- Having a compelling desire to improve and win in the marketplace
- In contributing positively not only in the workplace, but in our community and environment!
With rapid growth comes opportunity. We are looking for an Applied AI Engineer (LLM Applications Engineer) to join our team onsite in our Mississauga, Ontario Canada office! This is a full-time / exempt position.
Responsibilities:
- Design, build, and ship production-grade GenAI/LLM applications across Hygiena products including SureTrend - copilots, conversational agents and assistants, workflow automation, and decision support. Implement agentic workflows (tool use, multi-step execution, human-in-the-loop controls) with attention to reliability, safety, and clear failure modes.
- Design and build advanced retrieval and knowledge systems (RAG): hybrid search, vector and graph stores, indexing strategies, reranking, caching, and source attribution - grounding generation in authoritative sources such as regulatory frameworks (FSMA, HACCP, Codex), validation standards (AOAC, MicroVal, AFNOR), SOPs, and technical documentation.
- Engineer for production across the full SDLC (build → test → deploy → monitor → iterate). Implement MLOps/GenAIOps practices (CI/CD, reproducibility, environment parity, model/prompt/agent versioning) and build evaluation and observability for GenAI and agentic systems - tracing and instrumentation, regression test suites, automated scoring, and prompt/policy iteration loops.
- Security-test and red-team LLM and agentic systems - probing for prompt injection, jailbreaks, data/PII leakage, insecure tool use, and unsafe or non-compliant outputs; build adversarial test suites and harden systems and guardrails based on findings. Design for secure deployment with access controls, auditability, sensitive-data handling, and responsible-AI guardrails suited to a regulated domain.
- Configure and integrate AI solutions into enterprise and customer environments - APIs, data systems, and business applications (e.g., LIMS, QMS, ERP, and collaboration tools) - balancing quality, latency, cost, privacy, and adoption. Support data preparation, transformation, and validation that feeds retrieval, evaluation, and model training/deployment.
- Collaborate with Product Managers, Data Engineers, ML Engineering, and food safety scientists; translate ambiguous product and domain needs into clear technical requirements and tradeoffs; document patterns, decisions, and instrumentation; and stay current on emerging AI tools, models, and frameworks, bringing promising ones into real Hygiena use cases.
Qualifications:
- Bachelor’s Degree in Computer Science, Data Science, Engineering, or a related field, or equivalent practical experience; Master’s a plus.
- Minimum of 3–5 years of professional software, AI, or ML engineering experience, with strong backend engineering fundamentals.
- 1+ years of hands-on experience building and deploying LLM-powered applications in production, with real delivery considerations (latency, cost, reliability, security).
- Strong proficiency in Python and experience building APIs/services (e.g., REST/gRPC) and integrating with enterprise systems.
- Hands-on experience with at least one frontier GenAI platform - Anthropic, Google, or OpenAI - and its key building blocks (e.g., Claude API, Claude for Enterprise, tool use, extended thinking, Claude Code; Gemini API, Vertex AI Agent Builder, grounding; OpenAI Assistants/Responses APIs, Agents SDK).
- Experience building advanced retrieval/search systems (hybrid retrieval, vector search, reranking) and comfort working across multiple data stores (vector, graph, relational/document/search).
- Experience implementing agentic patterns (context management, memory/state, orchestration, and tool use).
- Familiarity with conversational AI frameworks (LLMs, chatbots, virtual assistants, agents) and their APIs.
- Experience with MLOps/LLMOps practices (evaluation frameworks, model monitoring, prompt management) on a platform such as Azure Machine Learning, and with LLM application frameworks/tooling (e.g., LangChain, LlamaIndex), preferred.
- Experience security-testing or red-teaming LLM/agentic systems (e.g., prompt injection, jailbreaks, data leakage), and familiarity with frameworks such as the OWASP Top 10 for LLM Applications, preferred.
- Experience with cloud environments (AWS, Azure, and/or Google Cloud), common platform services (storage, compute, IAM, networking), containers, and CI/CD preferred.
- Data engineering or data-science background (e.g., Spark, Airflow/dbt, feature engineering, experimentation, model evaluation), and experience in a regulated or safety-critical industry such as food safety, diagnostics, or life sciences, is advantageous but not required.
Skills:
- Strong product sense and a delivery mindset - takes ideas from proof-of-concept to MVP to production, designing for how real users will rely on AI outputs.
- Rigor around accuracy, traceability, safety, and security - designs for trust, guardrails, and graceful failure in a regulated, safety-critical domain.
- Comfortable with ambiguity and rapid iteration; able to prototype quickly, evaluate rigorously, and harden into reliable production code.
- Clear communication of technical and design decisions to diverse audiences, including Product, ML Engineering, Data, and Customers.
- Collaborative mindset; works effectively across Engineering, Data, Product, and food safety/domain teams.
- Intellectually curious and committed to staying current with advances in generative AI and applied LLM engineering.
- High ownership mentality - takes responsibility for the quality, reliability, and safety of the AI features they ship.
Why you’ll want to join Hygiena:
🚀 Teamwork as a core value
Our emphasis on teamwork and cross-functional communication enables us to build stronger bonds within our business.
🌍 Be a part of something big
We play a critical role in helping to prevent global health crisis such as foodborne illness, healthcare-associated infections, and other outbreaks.
💝 Giving back to our communities
We believe in giving back by supporting local organizations committed to improving the lives of children and youth in our communities.
We are an equal opportunity employer and value diversity. All employment is decided on the basis of qualifications, merit and business need. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran.
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