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Tiger Analytics

Forward Deployed Engineer (FDE) - GenAI / Agentic AI

  • Seen live on Tiger Analytics' site today
  • Mid level
Pay
Not stated
Location
Toronto, Ontario, Canada
Open for
9+ days
First seen
Oct 26, 2026
Apply on Tiger Analytics' site (opens in a new tab)

Posting record

No flags

Open 9+ days

The posting's record, oldest first
  1. Tiger Analytics' site dates the posting
  2. Ghostless first sees this listing
  3. Last checked: still up
How we know

It hasn't been reposted, listed twice, or left up unusually long, and the posting doesn't say it's a talent pool.

Ghostless records the day it first sees a posting, so a repost can't reset its age. This one was already up when Ghostless started tracking Tiger Analytics, so its true age is longer.

Last checked Nov 4, 2026.

How well do you match?

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What the posting discloses

Not stated: Pay, real vacancy, AI screening.

Why these three

Ontario requires postings from employers with 25 or more staff to state the pay, whether the vacancy exists, and whether AI screens applicants.

Some employers add pay only on their own site. Check the original posting before you rule it out.

Skills mentioned

About the role

Tiger Analytics is looking for experienced Forward Deployed Engineer with Gen AI experience to join our fast-growing advanced analytics consulting firm. Our employees bring deep expertise in Machine Learning, Data Science, and AI. We are the trusted analytics partner for multiple Fortune 500 companies, enabling them to generate business value from data. Our business value and leadership has been recognized by various market research firms, including Forrester and Gartner.

We are looking for top-notch talent as we continue to build the best global analytics consulting team in the world.

Role Overview

We're looking for a Forward Deployed Engineer who thrives at the intersection of client problem-solving and hands-on AI engineering. You'll partner directly with clients and engineering teams to turn complex business challenges into production-grade GenAI and Agentic AI solutions — owning the journey from first conversation to live deployment.

Requirements

  • Partner directly with clients to understand complex business problems and translate them into GenAI and Agentic AI solutions.
  • Design, build, deploy, and scale LLM applications, RAG systems, AI agents, and multi-agent workflows.
  • Integrate AI solutions with enterprise data, APIs, databases, and business applications.
  • Deploy, operate, and scale solutions in production cloud environments.
  • Troubleshoot and optimize production systems for performance, scalability, reliability, security, and cost.
  • Collaborate closely with architects, ML engineers, developers, and client stakeholders in fast-moving, ambiguous environments.

Qualifications

Engineering Foundation

  • 7+ years in software engineering, application development, ML engineering, or AI engineering.
  • Strong Python programming skills.
  • Solid grasp of APIs, system design, databases, cloud-native applications, and production deployments.
  • JavaScript/TypeScript experience is a plus.

GenAI / Agentic AI Expertise

  • Proven experience building and deploying end-to-end GenAI and/or Agentic AI solutions.
  • Hands-on experience with LLMs — OpenAI, Anthropic Claude, Google Gemini, and open-source models.
  • Hands-on experience with RAG, vector databases, embeddings, tool/function calling, and AI agents.
  • Experience with agent orchestration, multi-agent systems, or agentic workflows.
  • Familiarity with frameworks such as LangGraph, LangChain, LlamaIndex, Google ADK, or similar.
  • Working knowledge of MCP, A2A, or similar agent integration protocols.

Cloud & Production

  • Hands-on experience with at least one major hyperscaler — AWS, Azure, or GCP — including targeted expertise in:
  • AWS Stack: Designing workflows via Amazon Bedrock (Claude, Llama), deploying scalable RAG using OpenSearch Serverless (Vector Engine), and configuring Bedrock Guardrails for client VPCs.
  • Azure Stack: Deploying enterprise LLMs via Azure OpenAI Service (PTU optimization), building hybrid RAG systems with Azure AI Search, and orchestrating flows using Azure AI Foundry and Semantic Kernel.
  • GCP Stack: Scaling applications within Vertex AI, managing production pipelines, structuring enterprise RAG with Vertex AI Vector Search + BigQuery, and building agentic flows with Gemini APIs.
  • Exposure to LLM evaluation, observability, monitoring, guardrails, or LLMOps.

The FDE Mindset

  • Strong customer-facing communication and sharp problem-solving instincts.
  • Comfortable operating independently, navigating ambiguity, and moving fast from problem → solution → production.
  • Equally at home with business and technical stakeholders.

Benefits

This position offers an excellent opportunity for significant career development in a fast-growing and challenging 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.

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