About the role

Koda North is hiring a Senior AI Engineer to design, build, and improve practical AI-powered software systems. This role is for an experienced engineer who can turn business problems into reliable AI applications, not just prototypes. You will work on LLM-powered products, AI automation, retrieval workflows, document intelligence, data pipelines, model integrations, evaluation systems, and production-ready backend services. The ideal candidate has strong software engineering fundamentals, hands-on AI application experience, and the judgment to choose the right approach when working with imperfect data, changing requirements, latency limits, cost constraints, security needs, and production risk.

What you will do

Design and build production-ready AI applications, agents, and automation workflows
Develop LLM-powered features using modern AI APIs, frameworks, and backend systems
Build retrieval, search, RAG, document processing, and knowledge-based workflows
Design prompts, tools, evaluation flows, and guardrails for reliable AI behavior
Integrate AI systems with APIs, databases, business platforms, and internal tools
Build backend services that support AI features, data processing, and automation
Improve AI system accuracy, latency, cost efficiency, reliability, and maintainability
Create data pipelines for ingestion, cleaning, transformation, embedding, and retrieval
Evaluate model outputs, debug AI behavior, and improve system quality over time
Implement secure handling of sensitive data, permissions, logging, and access control
Collaborate with product, engineering, design, QA, and operations teams
Document AI architecture, technical decisions, system limits, and operational workflows

What we are looking for

8+ years of professional software engineering experience
Strong experience building production software systems, not only AI prototypes
Hands-on experience developing AI applications using LLMs and modern AI APIs
Strong backend engineering skills with Python and modern server-side development
Experience building APIs, data pipelines, integrations, and automation workflows
Experience with RAG, embeddings, vector databases, semantic search, or document intelligence
Strong understanding of prompt engineering, tool use, evaluation, and AI reliability patterns
Experience working with relational databases and structured or unstructured data
Ability to debug complex issues across AI behavior, backend systems, data quality, and production logs
Good understanding of security, privacy, access control, and responsible AI implementation
Ability to evaluate tradeoffs around model choice, latency, cost, accuracy, and maintainability
Experience with Git, code reviews, technical documentation, and team-based engineering workflows
Clear communication with product, technical, and non-technical stakeholders
Strong ownership mindset from technical discovery through production release and improvement

Nice to have

Experience in healthcare, healthtech, clinical workflows, patient-facing systems, or compliance-aware environments
Experience with HIPAA-conscious engineering, PHI handling, RBAC, audit logs, or privacy-sensitive AI systems
Experience with OpenAI API, Anthropic, Azure AI, AWS Bedrock, LangChain, LlamaIndex, or similar tools
Experience with vector databases such as Pinecone, Weaviate, Chroma, pgvector, or similar systems
Experience with fine-tuning, model evaluation, synthetic data, or human-in-the-loop review workflows
Experience with OCR, document extraction, classification, summarization, or data enrichment workflows
Experience with AWS, Docker, CI/CD, monitoring, observability, or cloud-based deployments
Experience building AI agents, workflow automation, copilots, chatbots, or decision-support tools
Experience with data governance, compliance-aware architecture, or secure enterprise integrations
Experience mentoring engineers or helping define AI engineering standards

Work schedule

Full time