Forward Deployed Engineer (FDE) - GenAI / Agentic AI

Posted Yesterday
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Toronto, ON, CAN
In-Office
Senior level
Big Data • Analytics • Business Intelligence • Big Data Analytics
The Role
Build and deploy production-grade GenAI and Agentic AI solutions for enterprise clients. Responsibilities include designing LLM applications, RAG systems, AI agents, and multi-agent workflows; integrating APIs, databases, and business applications; deploying and scaling cloud solutions; optimizing reliability, security, performance, and cost; and partnering with technical and business stakeholders from initial problem definition through production deployment.
Summary Generated by Built In

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.

Skills Required

  • 7+ years of experience in software engineering, application development, machine learning engineering, or AI engineering
  • Strong Python programming skills
  • Knowledge of APIs, system design, databases, cloud-native applications, and production deployments
  • Proven experience building and deploying end-to-end Generative AI or Agentic AI solutions
  • Hands-on experience with LLMs, including OpenAI, Anthropic Claude, Google Gemini, or open-source models
  • Hands-on experience with RAG, vector databases, embeddings, tool or function calling, and AI agents
  • Experience with agent orchestration, multi-agent systems, or agentic workflows
  • Familiarity with LangGraph, LangChain, LlamaIndex, Google ADK, or similar frameworks
  • Working knowledge of MCP, A2A, or similar agent integration protocols
  • Hands-on experience with at least one major hyperscaler: AWS, Azure, or GCP
  • Experience deploying, operating, and scaling AI solutions in production cloud environments
  • Exposure to LLM evaluation, observability, monitoring, guardrails, or LLMOps
  • JavaScript or TypeScript experience
  • Strong customer-facing communication and problem-solving skills
  • Ability to operate independently and work with business and technical stakeholders in ambiguous environments

Tiger Analytics Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Tiger Analytics and has not been reviewed or approved by Tiger Analytics.

  • Fair & Transparent Compensation — Feedback suggests pay is viewed as fair and market-aligned for many roles and geographies. Consistent, on-time pay and competitive packages in key markets reinforce a generally positive baseline.
  • Healthcare Strength — Feedback suggests U.S. medical coverage is strong, with administration via a known benefits platform and plan options seen positively. Health insurance is often regarded as a bright spot within the package.
  • Leave & Time Off Breadth — Feedback suggests generous PTO, paid sick days and holidays, and flexible PTO alongside remote-work options. These elements indicate broad time-off provisions available on paper.

Tiger Analytics Insights

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The Company
HQ: Santa Clara, CA
5,000 Employees
Year Founded: 2011

What We Do

Tiger Analytics is a global leader in AI and Analytics, helping Fortune 1000 companies solve their toughest challenges. We offer fullstack AI and analytics services & solutions to empower businesses to achieve real outcomes and value at scale. We are on a mission to push the boundaries of what AI and analytics can do to help enterprises navigate uncertainty and move forward decisively. Our purpose is to provide certainty to shape a better tomorrow. Our team of 4000+ technologists and consultants are based in the US, Canada, the UK, India, Singapore, and Australia, working closely with clients across CPG, Retail, Insurance, BFS, Manufacturing, Life Sciences, and Healthcare. We are Great Place to Work-Certified™ and have been recognized by analyst firms such as Forrester, Gartner, Everest, ISG, HFS, and others. Ranked among the ‘Best’ and ‘Fastest Growing’ analytics firms lists by Inc., Financial Times, Economic Times and Analytics India Magazine. In India, our offices are located in Chennai, Hyderabad and Bangalore.

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