Senior Agentic AI Data ScientistMindBridge Analytics • Ottawa, Ontario, Canada

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Senior Agentic AI Data Scientist

MindBridge Analytics

Ottawa, Ontario, Canada

Ottawa, Ontario, Canada

Postuler Maintenant

À propos

MindBridge is the global leader in AI-powered financial risk intelligence. Our platform, MindBridge AI is enabling finance and audit professionals to build the AI-powered finance department of the future. With over 120 billion financial transactions analyzed with MindBridge's AI, we set the standard for innovation, scalability, and customer satisfaction.

At MindBridge, we're driven by innovation and excellence, united as a team to revolutionize financial integrity. Here, your ideas matter, and your efforts make a meaningful impact. If you're passionate about using AI to drive positive change, MindBridge is the perfect fit. What distinguishes us is our unwavering commitment to our values: Innovation, Collaboration, and Integrity. These principles foster a vibrant workplace culture, where appreciation and a strong sense of community flourish.

About the Role

We're looking for a Senior Agentic AI Data Scientist to join MindBridge's Applied AI team. You'll design, build, and scale LLM-powered autonomous systems that reason, plan, and act across complex business workflows. Reporting to the AI Architect, you'll own the full lifecycle, from problem framing through deployment and governance. You'll partner closely with engineering and product teams to deliver production-grade agentic solutions.

What You'll Do
Agentic System Design & Development

Design and implement autonomous AI systems that reason, plan, and execute multi-step workflows toward business objectives

Architect multi-agent systems (planners, tool-callers, reviewers, supervisors) using orchestration frameworks such as LangGraph, LangChain, AutoGen, or similar

Build robust RAG pipelines, prompt strategies, and memory mechanisms to ground agent behavior in enterprise data

Develop guardrails, escalation paths, and human-in-the-loop patterns for safe, explainable agent behavior

Collaborate with the AI Architect to translate conceptual AI architectures into robust, scalable implementations

Data Science & Experimentation

Analyze large, multi-source datasets to identify high-impact opportunities for agentic automation

Build and maintain models that agents rely on (scoring, ranking, recommendation, policy models)

Design and execute experiments comparing agentic approaches against baselines, using rigorous statistical methods to quantify business impact

Production Engineering & MLOps

Build end-to-end pipelines for training, evaluation, deployment, and monitoring of agents and underlying models

Implement comprehensive observability: tracing, logging, cost tracking, and performance dashboards for agent behavior

Partner with platform teams to ensure scalability, reliability, and cost efficiency across cloud infrastructure, vector stores, and orchestration layers

Evaluation & Governance

Define evaluation frameworks and metrics: task completion rates, hallucination/error rates, escalation frequency, safety incidents, and business outcomes

Build offline evaluation datasets and online A/B tests for continuous improvement

Contribute to AI governance practices including documentation, system cards, and audit trails

What You'll Bring
Required

5+ years in applied ML, data science, or ML engineering with production systems experience

Strong Python proficiency and fluency with ML tooling (PyTorch, TensorFlow, NumPy, Pandas, or similar)

Hands-on experience with LLMs and generative AI (prompt engineering, RAG, fine-tuning)

Experience with agentic/orchestration frameworks or equivalent multi-step AI workflow development

Practical MLOps experience (MLflow, Kubeflow, Airflow, Vertex AI, SageMaker, or similar)

Solid software engineering fundamentals: version control, testing, CI/CD, code review

Preferred

Production experience with autonomous LLM/agentic systems

Knowledge of distributed systems and cloud platforms (AWS, GCP, Azure) with containerization (Docker, Kubernetes)

Background in RAG architectures, reinforcement learning, or multi-agent coordination

Experience with data platforms (warehouses, streaming systems, vector databases)

Familiarity with AI governance and risk management in enterprise/regulated environments

Track record of mentoring engineers and leading cross-functional initiatives

How You'll Succeed

You bridge the gap between experimental prototypes and hardened production systems

You communicate complex AI concepts clearly to both technical and non-technical stakeholders

You balance speed of iteration with robustness, security, and maintainability

Requirements Contingent on Employment

Fulfill requirements necessary to obtain and clear a full background check

Why You'll Love Being Part of Our Team: 

Competitive Compensation and Equity
 Flexible Work – Hybrid or Remote
 Comprehensive health benefits and wellness programs
 Professional development opportunities
 Flexible Time Off
 Company Matched Retirement Plans
 Unplug and recharge - 4 company-wide digital detox days annually   

Equal Opportunity at MindBridge: 

At the heart of our global success lies commitment to diversity and inclusion. We rigorously enforce an equal opportunity policy in all aspects of employment, championing merit and qualifications as our benchmarks. MindBridge is a proud equal opportunity employer, embracing applicants of all backgrounds without regard to race, nationality, religion, gender, disability, or any other factors.
At MindBridge, we are committed to providing an accessible candidate experience. If you require accommodations during the interview process or beyond, please inform us. We will work with you to provide necessary support and reasonable accommodations while maintaining confidentiality. Your comfort and participation are paramount to us. 

Please be advised that we may use AI tools in the processing of your application.

Ottawa, Ontario, Canada

Compétences linguistiques

English

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