4 months ago
Toronto, CanadaSenior
Responsibilities
- Contribute to AI and LLM-based system architecture and implement agentic AI components for workflow automation and task execution.
- Build and extend RAG-based solutions involving context retrieval, prompt workflows, system integration, and vector databases.
- Support batch and real-time inference pipelines with attention to performance, reliability, versioning, testing, and monitoring.
- Develop prototypes and proofs of concept, test agentic workflows and prompts, and iterate on retrieval strategies.
- Deploy AI platform components to development and production environments and assist with monitoring, troubleshooting, and performance improvement.
- Integrate AI components with APIs, data sources, cloud platforms, and enterprise systems.
- Collaborate with architects, engineers, data scientists, and product team members, and communicate technical concepts through documentation and presentations.
- Support junior team members, contribute to technical proposals or internal initiatives, and develop toward broader architectural responsibilities.
Requirements
- Bachelor’s degree in information technology, computer science, engineering, or a related field; a master’s degree is a plus.
- 4+ years of experience in software engineering, data engineering, or AI development.
- Solid foundation in software development and distributed systems concepts.
- Hands-on experience building or integrating AI/ML or LLM-based components.
- Proficiency in one or more programming languages such as Python or JavaScript is preferred.
- Hands-on experience with AI-assisted coding tools such as Cursor, Claude Code, Replit, or Lovable.
- Familiarity with AI frameworks and libraries such as LangChain, LlamaIndex, or Semantic Kernel.
- Working understanding of agentic AI concepts including RAG, prompt orchestration, vector databases, and basic multi-agent patterns.
- Basic understanding of cloud platforms and AI services, with experience in at least one hyperscaler environment.
- Exposure to deploying AI workloads on cloud platforms and integrating AI components with APIs and data sources.
- Familiarity with Docker and containerization concepts; Kubernetes exposure is a plus.
- Strong problem-solving, communication, code-quality, learning, collaboration, and iterative-delivery skills.
- GenAI fluency, including proven use of tools such as ChatGPT or Claude and response validation.
- Willingness to travel to work with clients and BCG teams as needed.
Benefits
- First-year base compensation of $160,000 CAD, plus an annual discretionary performance bonus and retirement contribution.
- BCG pays 100% of core health-benefit premiums for employees and eligible family members, with zero-dollar health insurance premiums.
- Prescription drug, telemedicine, mental-health, meditation, well-being, dental, orthodontia, vision, and flexible-spending benefits.
- Annual retirement contributions, whether or not the employee contributes, plus an RRSP contribution option.
- Paid parental and family-care leave and reimbursement for fertility, surrogacy, and adoption expenses.
- Paid time off includes 10 public holidays, 2 floater days, office closure between Christmas and New Year’s, 15 vacation days annually, and paid sick time.
- Opportunity to work across BCG disciplines with a team delivering hands-on digital and AI solutions.
- Travel to clients and BCG teams may be required.
Tech Stack
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