AI Developer building agentic systems, RAG pipelines, and production AI solutions for Mirego clients. Bridging backend software development with modern AI models and frameworks.
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
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