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About the role

  • Senior AI Engineer building production generative AI and agentic systems for Lantern’s specialty healthcare platform. Leading LLM architecture, LLMOps, technical reviews, and engineering mentorship in regulated healthcare.

Responsibilities

  • Architect and deliver production LLM-powered capabilities including advanced RAG pipelines, structured extraction, multi-document reasoning, dialogue systems, and domain-specific language models
  • Own prompt engineering strategy and establish standards for prompt management, evaluation, and continuous improvement
  • Lead selection and integration of embedding models, vector databases, and hybrid retrieval architectures
  • Define LLM evaluation frameworks, quality benchmarks, guardrails, grounding strategies, and hallucination mitigation controls
  • Evaluate frontier and open-source models and lead model selection decisions
  • Lead architecture and implementation of production agentic systems with orchestration, planning, tool use, memory, and state persistence
  • Design human-in-the-loop mechanisms, approval workflows, fallback strategies, and audit trails
  • Establish reliable tool-use and function-calling patterns for external APIs, clinical systems, and internal data services
  • Define agent observability standards including trace logging, monitoring, drift detection, and structured evaluation
  • Write production-quality, modular, well-tested code and lead design and code reviews
  • Architect and maintain LLM inference services, API integrations, and Azure data pipelines
  • Define and champion LLMOps practices including prompt versioning, experiment tracking, model registration, A/B testing, CI/CD, and regression testing
  • Establish production monitoring and observability for latency, quality, cost, safety, and behavioral drift
  • Lead technical documentation including architecture decision records, runbooks, model cards, and evaluation playbooks
  • Partner with product, clinical operations, marketing, and data teams to translate requirements into AI initiatives
  • Mentor junior and mid-level engineers and elevate engineering standards
  • Lead architecture discussions, contribute to the AI engineering roadmap, and represent the team’s technical perspective
  • Drive organizational adoption of GenAI and agentic capabilities

Requirements

  • Bachelor’s or Master’s degree in Computer Science, Engineering, or equivalent practical experience
  • 5+ years of experience building and deploying production AI/ML systems, with at least 2–3 years focused on LLM and GenAI applications
  • Strong proficiency in Python and software engineering fundamentals, including testing, modular design, code reviews, documentation, and version control
  • Deep hands-on experience with LLM APIs and advanced prompt engineering
  • Proven experience designing and deploying production RAG systems
  • Hands-on experience with agentic frameworks and production deployment of multi-step agent workflows
  • Experience with LLM evaluation tooling and systematic output-quality improvement
  • Experience with cloud platforms, preferably Azure, and containerized deployment using Docker and Kubernetes
  • Familiarity with LLMOps/MLOps tooling such as MLflow, Azure ML, and Weights & Biases
  • Strong communication and collaboration skills, with ability to lead technical discussions and influence cross-functional partners
  • Track record of mentoring engineers and elevating team engineering standards
  • Preferred additional experience with regulated-industry AI safety, grounding, compliance controls, fine-tuning, RLHF, DPO, LoRA, QLoRA, healthcare data, multi-agent systems at scale, streaming pipelines, real-time inference, event-driven architectures, open-source contributions, research publications, or conference presentations

Benefits

  • Medical Insurance
  • Dental Insurance
  • Vision Insurance
  • Short- & Long-Term Disability
  • Life Insurance
  • Flexible PTO
  • RRSP with company match

Job title

Job type

Full Time

Experience level

Senior

Salary

Not specified

Degree requirement

Bachelor's Degree

Tech skills

AzureCloudDockerKubernetesPython

Location requirements

HybridVancouverCanada

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