Senior AI Engineer

🕒 April 26

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Blanc Labs

WebsiteLinkedInAll Job Openings

51 - 200 employees

🤝 B2B

💸 Finance

☁️ SaaS

💰 Venture Round on 2016-12

B2B • Finance • SaaS

Blanc Labs is a full-service technology consulting firm focused on helping clients realize their full potential through the creative use of technology. They specialize in digital transformation, technology strategy and implementation, API management, AI, analytics, and automation. Their services include systems integration and business process improvement, especially in the financial services and healthcare sectors. Blanc Labs partners with industry leaders to enable innovative customer experiences and achieve measurable business outcomes, with a strong presence in the Canadian market.

📋 Description

• Build and deliver AI-powered features based on functional and technical requirements provided by TPMs and Principal AI Engineers • Develop end-to-end AI solutions, including backend services, APIs, and application-layer integrations • Integrate large language models (LLMs) into production systems, ensuring performance, scalability, and reliability • Design, test, and optimize prompts to improve output quality and consistency • Collaborate with ML Engineers to embed models trained or fine-tuned on proprietary data into applications • Participate in model evaluation and validation, ensuring outputs meet quality, accuracy, and performance benchmarks • Support testing and deployment of AI features through CI/CD pipelines • Troubleshoot and refine AI behaviours in real-world production scenarios.

🎯 Requirements

• Strong experience in software engineering, with a focus on backend development (Python preferred) • Hands-on experience working with large language models (e.g., OpenAI, Anthropic, open-source LLMs) • Experience designing and integrating APIs and microservices • Familiarity with prompt engineering and LLM optimization techniques • Understanding of model evaluation frameworks and performance metrics • Experience working with ML Engineers or deploying ML models into production environments • Knowledge of CI/CD pipelines and modern deployment practices • Strong problem-solving skills and ability to work in a fast-paced, collaborative environment • Nice-to-Have: Experience with vector databases, embeddings, and retrieval-augmented generation (RAG) • Exposure to fine-tuning models or working with proprietary datasets • Familiarity with cloud platforms (AWS, GCP, or Azure) • Experience building scalable AI/ML systems in production