Senior Artificial Intelligence/Machine Learning Engineer

Ciklum • Canada,

1d • Onsite

About The Position

As a Senior Artificial Intelligence/Machine Learning Engineer, become a part of a cross-functional development team, engineering experiences of tomorrow. We are placing senior AI engineers to design and deliver production agentic AI systems for an enterprise client.

Requirements

• 3+ years building with LLMs in production systems that real users depend on
• Hands-on experience designing agentic workflows: tool and function calling, retrieval-augmented generation (RAG), multi-step orchestration, and memory
• Deep practical experience with the OpenAI API and GPT Enterprise: model selection, prompt engineering, structured outputs, function calling, cost and latency tuning, and data-handling controls
• Strong prompt-engineering discipline and an evaluation-first approach, measuring agent quality with evals rather than by inspection
• Direct, hands-on production experience with the Glean platform: Agent Builder, Apps, Actions, Model Hub, connectors, and permission-aware retrieval (non-negotiable)
• Working knowledge of enterprise search and RAG architecture on Glean: indexing, connectors, retrieval quality, and runtime permission enforcement
• Production experience deploying and operating services on AWS and/or GCP, with comfort across both preferred. IAM, secrets management, networking, and cost awareness
• Strong software engineering fundamentals in Python or equivalent: clean, tested, maintainable code, API design, CI/CD, and version control
• Experience integrating enterprise SaaS systems through API (for example Jira, Slack, Google Workspace, ticketing and GRC tools), including auth flows and webhook and event patterns
• Data engineering competence: moving and transforming data between systems, working with warehouses, and handling sensitive data securely

Nice To Haves

• Experience locking down and governing enterprise tools, including controlled intake, permission models, and audit trails
• Familiarity with observability and incident response for AI systems: monitoring drift, alerting, and root-cause analysis
• Exposure to regulated or finance and accounting environments where auditability and data governance matter
• Prior consulting or client-facing delivery experience and comfort working embedded with a client’s teams

Responsibilities

• Build autonomous agents on the client’s existing enterprise AI stack
• Own agents from design through production, monitoring, and iteration
• Approach agents as production software
• Work in terms of triggers, retrieval, reasoning steps, actions, permissions, evaluation, and observability, and know how to make an agent reliable, secure, and maintainable at enterprise scale
• Build for maintainability, favoring configuration over custom code and shared services over one-offs, keeping the bespoke surface area small
• Ensure security and governance by default, handling credentials, permissions, and sensitive data correctly without being prompted, and designing for audit from the start
• Be pragmatic and scale-aware, designing around real platform limits such as tool-call budgets, payload caps, and rate limits before they become production problems
• Provide client-ready communication, able to explain an architecture decision to a technical buyer, defend it under questioning, and write clearly

Benefits

• Healthcare
• Basic Life Insurance
• Short and Long-term disability insurance according to the Company’s Benefit Plans
• Internal events (meetups, conferences, workshops)
• Udemy access
• Language courses
• Company-paid certifications

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Education Level: No Education Listed