Software Engineer

Position Overview

As a Senior Staff Software Engineer on Diligent's Platform AI team, based out of our technical center of excellence in Vancouver, you will drive the architecture and technical direction of the services that bring AI research and models into production across Diligent's global product suite.

You will partner with AI researchers, product managers, and Staff Engineers as peers — leading through influence across the Platform AI organization rather than through reporting authority, on secure, scalable AWS Serverless solutions that translate ML and LLM research into commercial-quality, production systems.

Key Responsibilities

• Drive technical direction and architecture for ML/LLM systems across multiple AI platform teams, partnering with Staff Engineers rather than managing ICs in isolation.
• Design secure, scalable, fault-tolerant AI/ML solutions using AWS Serverless technology — event-driven, highly observable, with infrastructure as code.
• Evaluate and prototype new AI technologies (LLM frameworks, model providers, agentic tooling) to guide build-vs-buy decisions across the organization.
• Serve as the go-to contact for architecture problems and questions across the Platform AI org, and regularly present and guide architecture discussions department-wide.
• Mentor Staff Software Engineers and Applied Scientists through constructive code review and design partnership.
• Collaborate with Applied Scientists and Product teams to productize AI capabilities, translating multi-quarter AI strategy into execution roadmaps and representing engineering's perspective to senior leadership.
• Design, build, and scale search and retrieval systems — including OpenSearch and semantic/vector search — that power discovery, retrieval-augmented generation, and other AI-driven product features.
• Lead through ambiguity, helping teams navigate undefined problems to successful delivery.

Required Experience/Skills

• 10-15+ years of professional experience developing and owning high-scale, secure cloud applications, including a demonstrated track record operating at Staff level across multiple teams.
• Strong proficiency in Python and its data science libraries/frameworks (pandas, NumPy, scikit-learn), with code that adheres to SOLID principles.
• Experience with infrastructure-as-code practices in AWS (CDK, Terraform, or CloudFormation) or similar.
• Hands-on experience with LLMs, including prompt engineering, fine-tuning, model evaluation, and RAG-based functionality.
• Hands-on experience with search technologies, including OpenSearch/Elasticsearch, semantic search, and vector embeddings.