Design, develop, and implement GenAI solutions for various financial applications, including personalized recommendations, risk assessment, fraud detection, and automated reporting.
Design and implement AI Agents, utilizing rigorous harness engineering to build the necessary guardrails, memory management, and tool orchestration for safe and reliable execution.
Process and analyze large datasets of structured and unstructured data.
Architect and scale dynamic context retrieval systems (RAG) and semantic search infrastructures, leveraging tools like AWS Bedrock and LangGraph to securely ground AI outputs in enterprise data
Develop and refine advanced prompting strategies for LLMs.
Test, evaluate, and analyze the performance of LLM and other GenAI models.
Collaborate closely with engineering teams to deploy and maintain GenAI models in production environments, including containerization, CI/CD pipelines, and cloud infrastructure management.
Communicate effectively with business stakeholders.
Stay up-to-date with the latest advancements in GenAI research and development, including areas like Agentic AI.

Bachelor’s degree in Computer Science, Software Engineering, or a related field
5 years+ of experience in DevOps, Software Development, or AI/ML development, with a proven track record of building and deploying sophisticated GenAI applications
Deep understanding of GenAI models, architectures and agentic AI concepts
Extensive experience of LLM architectures, prompt engineering, fine-tuning, evaluation, and deploying agents (Agentcore stack)
Expert Python skills, Vector Databases (Qdrant, Pinecone, pgvector), and RAG pipelines using LlamaIndex and LangGraph
Experience in MLOps, containerization (Docker/Kubernetes), CI/CD, and cloud infrastructure (AWS, Azure, or GCP)
Analytical problem-solver with a proven ability to effectively communicate and collaborate across departments and drive projects forward

**Strongly Preferred Experience: **

Experience with financial data and applications
Familiarity with chatbot development frameworks and best practices, including conversational AI design and natural language understanding (NLU)
Experience leading or contributing to complex data science or AI/ML projects in a fast-paced environment
Experience with data visualization and reporting tools
Experience with SQL databases

An award-winning culture with a collaborative & inclusive team.
Competitive pay and performance-based bonus:
Annual Base Salary: $130,000
145,000
Annual Bonus: 20%
Committed to flexible work arrangements, offering hybrid workplace options.
Comprehensive medical, dental and vision coverage + Lifestyle Account.
RRSP Matching and Parental Leave Top UP Program.
In office massage, meditation & workout sessions.
Virtual events such as Lunch & Learns, company parties, fun team activities and charity initiatives.
Career learning and development programs.

Senior DevOps Engineer, AI Infrastructure

Key skills