- Company Name
- Ascend
- Job Title
- Senior Product Engineer - Canada
- Job Description
-
**Job Title:** Senior Product Engineer
**Role Summary:**
Lead the design, development, and delivery of AI‑powered products utilizing Large Language Models (LLMs) and Machine Learning (ML). Collaborate with cross‑functional teams (product, design, data science) to build secure, scalable, and high‑availability systems that redefine accounting workflows. Drive engineering excellence through modern tooling, rapid velocity, and best‑practice processes.
**Expectations:**
- Deliver production‑ready code with high quality, reliability, and security.
- Own technical architecture and maintainability of AI features.
- Mentor peers, advocate for clean design, and uphold coding standards.
- Influence product direction through data‑driven insights and stakeholder communication.
**Key Responsibilities:**
1. Architect and implement LLM‑enabled features that meet user needs and performance targets.
2. Build and maintain ML/LLM experimentation pipelines, including real‑time evaluation, observability, and human‑in‑the‑loop workflows.
3. Develop scalable, secure backend services on cloud platforms (AWS, GCP, or Azure) with CI/CD, automated testing, and observability tooling.
4. Experiment with AI‑powered development tools (IDE extensions, code‑gen assistants, automated review) to increase engineering velocity.
5. Champion best practices in coding, testing, security, and scalability; establish repeatable engineering processes.
6. Collaborate with product managers and designers to translate requirements into high‑level designs and API contracts.
7. Conduct code reviews, performance profiling, and troubleshooting to ensure uptime and stability.
**Required Skills:**
- 5–7+ years of software development experience in dynamic, high‑performance teams.
- Deep knowledge of LLMs, transformer models, and ML inference pipelines.
- Proficiency in at least one modern programming language (Python, Java, Go, TypeScript).
- Hands‑on experience with cloud platforms (AWS, GCP, Azure) – compute, storage, data pipelines, and ML services.
- Strong background in distributed systems, microservices, and REST / gRPC APIs.
- Experience with DevOps tools: Docker, Kubernetes, Helm, Terraform, GitOps.
- Familiarity with CI/CD, automated testing, static analysis, and security scanning.
- Knowledge of data privacy standards (GDPR, CCPA) and secure coding principles.
- Excellent problem‑solving, communication, and collaboration skills.
**Required Education & Certifications:**
- Bachelor’s degree in Computer Science, Software Engineering, Information Technology, or related field.
- Master’s degree or higher is a plus.
- Relevant certifications (AWS Certified Solutions Architect, GCP Professional Cloud Architect, Azure Solutions Architect, etc.) are beneficial but not mandatory.