5 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
Categories
About BCG
Boston Consulting Group provides management consulting, technology, and design services to large enterprises, governments, and nonprofits, helping with strategy, digital transformation, and operations. The firm works on a project-based, fee-for-service model and also incubates products and ventures through BCG X. Founded in 1963 and headquartered in Boston, it is a global partnership with offices worldwide.