1 день назад
Applied AI Engineer (Agentic Workflows & RAG) - Masters-Level Internship
32$
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Описание вакансии
Текст:
TL;DR
Applied AI Engineer (Agentic Workflows & RAG) - Masters-Level Internship (Agentic Workflows, RAG, and LLM Evaluation): Building production AI workflows, retrieval pipelines, and model integrations for real client use cases with an accent on reliable agent behavior, model selection, prompt engineering, and evaluation. Focus on grounding model outputs in current data, connecting AI tools to internal systems through APIs or MCP, and validating non-deterministic outputs for correctness, security, and safety.
Location: Remote, with hybrid options in Toronto
Compensation: $32 per hour
Company
is a Toronto-based language synthesis AI company building technology that removes language barriers and enables access to information in any language.
What you will do
- Design, build, and harden agentic workflows that plan and take reliable actions.
- Build production retrieval-augmented generation and search pipelines that ground model outputs in client data.
- Select reasoning or instruction-tuned models and justify trade-offs across latency, cost, and quality.
- Engineer prompts and context structures for different model classes.
- Create evaluation harnesses, test sets, and regression checks for non-deterministic AI features.
- Integrate AI tools with internal systems and data sources through APIs, MCP, and tool calling.
Requirements
- Master’s degree enrollment or completion is mandatory in computer science, software engineering, AI/ML, information systems, or a related field.
- Hands-on experience with AI coding assistants and the Claude API or comparable model APIs.
- Understanding of LLM and reasoning-model behavior, including context windows and model selection.
- Practical experience with an agentic workflow, RAG pipeline, or model integration using tool calling or MCP.
- Fluency in JavaScript/React and/or Python sufficient to build, evaluate, and fix AI-generated output.
- Strong prompt engineering, context management, evaluation, communication, and collaboration skills.
Nice to have
- Portfolio, GitHub repository, or live examples demonstrating AI engineering work.
- Experience with vector databases such as pgvector, Pinecone, or Weaviate.
- Experience with Next.js, Node.js, Supabase, Firebase, PostgreSQL, or agent frameworks.
Culture & Benefits
- Work inside a startup preparing for an IPO.
- Work directly with senior management and advisory board members.
- Build real projects with measurable outcomes and take ownership of impactful work.
- Work with colleagues from different backgrounds, disciplines, and countries in an inclusive environment.
- Duration: 520 hours, completed over 3 months full-time or 6 months part-time.
Hiring process
- Application followed by first, second, and third interviews.
- Group discovery session and next-step form.
- Contract and onboarding.
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