Tiger Analytics

AI Engagement Lead

Canada full-time Executive Salary not listed
full-time Executive level Technology & IT Curated
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About the role

Tiger Analytics is an advanced analytics consulting firm. We are the trusted analytics partner for several Fortune 100 companies, enabling them to generate business value from data. Our consultants bring deep expertise in Data Science, Machine Learning, and AI. Our business value and leadership have been recognized by various market research firms, including Forrester and Gartner.
We are looking for an AI Engagement Lead / AI Engineering Pod Lead who can combine strong client and project leadership with hands-on expertise in AI/ML and Generative AI engineering. The role will involve approximately 50% engagement/project management and coordination and 50% hands-on technical leadership and AI engineering.
Responsibilities:

Lead AI/GenAI engagements from discovery and solution definition through development, deployment, and production.

Serve as the primary technical and delivery interface for clients and senior stakeholders.

Understand business objectives and translate them into AI/ML solution requirements and actionable engineering plans.

Own project planning, prioritization, timelines, milestones, risks, dependencies, and overall delivery.

Coordinate across AI Engineers, Data Scientists, Data Engineers, Product Managers, and client teams.

Conduct regular client discussions, status reviews, technical walkthroughs, and solutioning sessions.

Proactively identify delivery risks, technical challenges, resource constraints, and dependencies and drive them toward resolution.

Architect, develop, and deploy AI/ML and Generative AI solutions for enterprise use cases.

Lead hands-on development of LLM-powered applications, RAG systems, AI agents, and agentic workflows.

Design and implement end-to-end AI application architectures, including: LLM integration, Prompt engineering, RAG pipelines, Embeddings and vector databases, Tool/function calling, Agent orchestration, Evaluation and monitoring

Work with frameworks such as LangChain, LangGraph, LlamaIndex, Semantic Kernel, or equivalent technologies.

Integrate foundation models and LLM platforms such as OpenAI, Azure OpenAI, Anthropic Claude, Amazon Bedrock, Gemini, or open-source models.

Develop production-grade AI services and APIs using technologies such as Python, FastAPI, Docker, Kubernetes, and cloud platforms.

Design retrieval pipelines including document processing, chunking, embedding generation, vector search, hybrid retrieval, and re-ranking.

Requirements

10+ years of experience in software engineering, AI/ML engineering, data science, or a related technical field.

Strong hands-on experience building and deploying AI/ML or Generative AI solutions.

Proven experience leading technical teams or AI engineering pods while remaining hands-on.

Strong proficiency in Python and experience developing production-grade applications.

Strong understanding of LLMs, Generative AI, NLP, RAG, and AI agents.

Experience with one or more AI/GenAI frameworks such as LangChain, LangGraph, LlamaIndex, Semantic Kernel, or equivalent.

Experience working with LLM APIs/foundation models such as OpenAI, Azure OpenAI, Anthropic, Bedrock, Gemini, or open-source LLMs.

Experience with vector databases and semantic search.

Experience designing and deploying cloud-based AI solutions on AWS, Azure, or GCP.

Strong understanding of APIs, microservices, Docker, CI/CD, and production deployment.

Experience with AI evaluation, monitoring, guardrails, and responsible AI is highly desirable.

Strong client-facing communication and stakeholder management skills.

Demonstrated ability to translate ambiguous business problems into practical technical solutions.

Master's in Business Analytics or equivalent work experience.

Benefits
Significant career development opportunities exist as the company grows. The position offers a unique opportunity to be part of a small, fast-growing, challenging and entrepreneurial environment, with a high degree of individual responsibility.
Tiger Analytics provides equal employment opportunities to applicants and employees without regard to race, color, religion, age, sex, sexual orientation, gender identity/expression, pregnancy, national origin, ancestry, marital status, protected veteran status, disability status, or any other basis as protected by federal, state, or local law.
Originally posted on Himalayas

Interview prep

Walk in with sharper answers.

Use this as a quick practice sheet before you speak with the employer.

Executive
Technology & IT API integration Data Analysis Project Management Python Executive level full-time

Likely questions

  1. Tell us about work you have done that is close to the AI Engagement Lead role.
  2. How would you approach your first 30 days at Tiger Analytics?
  3. Which of API integration, Data Analysis and Project Management have you used recently, and what did it help you achieve?
  4. How have you led people, improved a process, or made a hard decision in a previous role?
  5. How do you handle busy days, changing priorities, or pressure at work?

Prepare before the call

  • A recent example that proves your experience with API integration, Data Analysis and Project Management.
  • One short story with a problem, your action, and the result.
  • Two examples that show the strengths listed on your CV.
  • A clear reason why this role and company interest you.
  • Your availability, preferred work style, and salary expectations.

Ask them

  • What would success look like in the first 90 days?
  • What are the main problems this hire should help solve?
  • How does the team give feedback and measure good work?
  • What does a normal working week look like for this role?
Practice line

I am interested in the AI Engagement Lead role because I can bring practical experience in API integration, Data Analysis and Project Management, learn the team quickly, and contribute to the outcomes Tiger Analytics needs from this hire.

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