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Tiger Analytics

Delivers Data and AI transformation

AI Engagement Lead

AI Application EngineeringConfirmed live in the last 24 hours
Full-timeToronto, ON, CanadaNo salary listedRemote

About the Job

Requirements

  • At least 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.
  • 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 large language models, Generative AI, natural language processing, retrieval-augmented generation, and AI agents.
  • Experience with one or more AI/Generative AI frameworks such as LangChain, LangGraph, LlamaIndex, or Semantic Kernel, or equivalent.
  • Experience working with large language model APIs and foundation models such as OpenAI, Azure OpenAI, Anthropic, Amazon Bedrock, Gemini, or open-source large language models.
  • Experience with vector databases and semantic search.
  • Experience designing and deploying cloud-based AI solutions on AWS, Azure, or Google Cloud Platform.
  • Strong understanding of APIs, microservices, Docker, continuous integration and continuous delivery, and production deployment.
  • Strong client-facing communication and stakeholder management skills.
  • Ability to translate ambiguous business problems into practical technical solutions.
  • Master's degree in Business Analytics or equivalent work experience.

Responsibilities

  • Lead AI and Generative AI 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.
  • 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 large-language-model-powered applications, retrieval-augmented generation systems, AI agents, and agentic workflows.
  • Design and implement end-to-end AI application architectures, including large language model integration, prompt engineering, retrieval-augmented generation pipelines, embeddings and vector databases, tool/function calling, agent orchestration, evaluation, and monitoring.
  • Work with AI frameworks such as LangChain, LangGraph, LlamaIndex, Semantic Kernel, or equivalent technologies.
  • Integrate foundation models and large language model platforms such as OpenAI, Azure OpenAI, Anthropic Claude, Amazon Bedrock, Gemini, or open-source models.
  • Develop production-grade AI services and APIs using Python, FastAPI, Docker, Kubernetes, and cloud platforms.
  • Design retrieval pipelines including document processing, chunking, embedding generation, vector search, hybrid retrieval, and re-ranking.

Desired Qualifications

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

About the Company

Tiger Analytics

Delivers Data and AI transformation

Tiger Analytics helps large organizations plan and execute Data and AI–led transformations at scale. It works with clients to translate business needs into data and AI initiatives, using an approach that combines business value mapping, agile operating models, and a platforms-based architecture, backed by partnerships with major hyperscalers. The company designs and delivers end-to-end data and AI solutions—from strategy and data engineering to model development and deployment—so that AI can be applied to tough, real-world problems. Unlike firms that rely mainly on standard playbooks, Tiger Analytics builds custom approaches and accelerators to suit each client’s value chain and operating model. With a global team of 5000+ technologists and consultants, the goal is to enable measurable value and practical outcomes through data and AI programs that work at enterprise scale.

Company size
1,001-5,000
Company stage
Not listed
Total funding
Not listed
Headquarters
San Jose, CA
Founded
2010

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