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AI Engineer

CanadaCanada
United StatesUnited States
Full-time
Not Disclosed
Senior-Level

Job Description

Key Skills Required

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Machine LearningBestseller 🔥
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AWSAI EngineerGenerative AI

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The Role

We are looking for a highly skilled AI Engineer with 7+ years of experience in software engineering, with a heavy focus on Python, AWS infrastructure, and Generative AI.

The ideal candidate will be responsible for building high-performance API services and implementing complex RAG and Agentic AI architectures.

Requirements

Key Requirements:

  • Experience: Minimum of 7+ years of professional experience in software development and AI engineering.
  • Generative AI Integration: Hands-on experience integrating Generative AI/LLM APIs, AWS Bedrock, and other model providers.
  • Infrastructure & DevOps: Experience with DevOps, CI/CD pipelines, and ML pipelines within the AWS ecosystem.
  • Agentic AI: Exposure to building Gen AI/Agentic AI applications, managing efficiency, latency, and backend infrastructure.
  • Technical Standards: Strong Python programming skills with a deep understanding of OpenAI API standards, JSON RESTful design, and LLM orchestration.
  • Preferred Skills: Experience working with Bedrock Agent/Core services is a significant plus.

Candidates will be expected to demonstrate deep technical proficiency in the following areas:

1. Retrieval-Augmented Generation (RAG)

  • Ability to design and implement end-to-end RAG pipelines, including retrievers, vector stores (e.g., Pinecone, Weaviate, or pgvector), and generators.
  • Expertise in latency optimization and relevance tuning to ensure production-grade performance.
  • Strategic approach to document chunking and embedding, balancing granularity with semantic coherence.

2. Agent Development

  • Practical experience developing autonomous or semi-autonomous agents using frameworks such as LangChain, CrewAI, or Semantic Kernel.
  • Ability to manage orchestration, tool integration, and robust error handling for non-deterministic AI outputs.
  • Proficiency in managing memory and context (episodic vs. long-term) in multi-turn interactions and external API interfacing.

3. Evaluation and Optimization

  • Familiarity with evaluation frameworks (e.g., RAGAS, TruLens) to assess performance, grounding accuracy, and hallucination detection.
  • Ability to iterate systems based on performance metrics and continuous improvement practices.

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.

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