About the company

At Accentrust, we are an agile tech startup dedicated to building scalable and innovative software solutions that solve complex data challenges. Headquartered in Vancouver, our passionate team leverages cutting-edge technologies, including Generative AI and Large Language Models (LLMs), to create impactful, data-driven solutions for diverse industries.

At the heart of our approach is a commitment to developing systems that enhance operational efficiency and deliver critical business insights. Our collaborative team of software engineers, data scientists, and problem solvers specializes in integrating advanced machine learning algorithms, Generative AI, and LLMs into robust and efficient data pipelines. This empowers our clients to achieve higher productivity, informed decision-making, and substantial business value.

Accentrust doesn't just keep up with technological advancements—we actively shape the future of data-driven innovation. Through our expertise in AI and comprehensive data solutions, we strive to continuously unlock new potential for businesses in the evolving digital landscape.

Job overview

• Build and operate production AI capabilities within Accentrust’s enterprise SaaS platform.

• Own backend services and AI workflows end-to-end (design → implementation → deployment → operations).

• Deliver secure, scalable, and measurable AI systems (quality, latency, cost, and reliability).

• Collaborate cross-functionally with Product, Security/Compliance, and Customer Engineering.

Job description

As a Software Development Engineer (AI) at Accentrust, you will develop the core software systems that bring AI features into production for enterprise customers. This role is engineering-first and hands-on: you will design and implement cloud-native services, integrate LLM/ML capabilities into product workflows, and ensure systems meet enterprise expectations for security, governance, and reliability.

You will work closely with Product to translate customer problems into shippable functionality and with Security/Compliance to ensure safe handling of data, robust access control, and auditability. You will also partner with Customer Engineering to support production readiness and successful launches, while keeping your focus on building durable platform and product components—not consulting deliverables.

Success in this role means shipping AI features that customers adopt, maintaining strong operational excellence (SLOs, monitoring, incident response), and continuously improving AI quality with evaluation, experimentation, and feedback loops.

Responsibilities

• Build AI features for production: Develop backend services and APIs that power AI-driven product experiences (e.g., retrieval, agents, summarization, classification, search, automation).

• Ship reliable AI systems: Own deployment, monitoring, alerting, and incident response for AI services with clear SLOs/SLAs.

• Design scalable architecture: Create cloud-native, distributed components that scale securely for enterprise workloads.

• Implement MLOps practices: Automate CI/CD for models and pipelines, manage versioning, rollouts, A/B tests, canary deployments, and rollback strategies.

• Integrate with customer environments: Support enterprise integrations (SSO, data sources, event streams, private networking) while meeting security and compliance requirements.

• Evaluate and improve quality: Build evaluation harnesses, offline/online metrics, human-in-the-loop workflows, and regression testing to prevent quality drift.

• Partner cross-functionally: Work with Product/Design to turn requirements into deliverables; collaborate with Security/Compliance to meet governance needs; coordinate with Customer teams on production readiness.

• Create reusable engineering assets: Produce templates, reference implementations, internal libraries, and runbooks that accelerate delivery and maintainability.

Qualifications

• 3+ years of professional software engineering experience (backend, platform, or distributed systems).

• Strong proficiency in one or more of: Python, TypeScript/Node.js, Java, Go (or similar).

• Experience building and operating cloud services (AWS, Azure, or GCP), including networking, observability, and scalability patterns.

• Hands-on experience implementing AI/ML-enabled systems, such as: LLM integration and orchestration Retrieval (vector search), RAG pipelines, embeddings Data-intensive processing (streaming/batch), feature stores, or analytics pipelines Solid understanding of security fundamentals (authn/authz, least privilege, secrets management, secure API design).

• Ability to communicate technical tradeoffs clearly to both engineering peers and non-technical stakeholders.

Bonus if you have

• Experience delivering in regulated industries (financial services, healthcare, public sector) and working under compliance constraints (SOC 2, ISO 27001, HIPAA, PCI, etc.).

• Familiarity with identity and access management patterns: SSO (SAML/OIDC), SCIM, RBAC/ABAC, policy enforcement.

• Experience with model lifecycle concerns: prompt/version management, guardrails, safety filters, PII handling, audit logging, and governance.

• Production experience with Kubernetes, service meshes, IaC (Terraform), and modern observability stacks.

• Cloud certifications (AWS/Azure/GCP) are a plus.

What we offer

• Top-tier compensation with performance bonus.

• Comprehensive health and wellness package.

• Remote-first setup with travel support.

• Professional development budget and certification reimbursement.

• Flexible PTO and paid family leave.

Equal opportunity statement

At Accentrust, we believe in an inclusive and equitable workplace. We welcome applicants from all backgrounds, including women, visible minorities, Indigenous peoples, persons with disabilities, and individuals of all gender identities and expressions. All qualified applicants will receive consideration without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex, sexual orientation, or any other characteristic protected by applicable local laws and regulations.