AI Application Engineer
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Job Description
AI Application Engineer focusing on AI application development and machine learning at Rearc. Collaborating on GenAI projects that push AI capabilities in customer environments.
Responsibilities:
- Collaborate with Colleagues – Work closely with colleagues to understand customers' business objectives and technical challenges, contributing to the design and development of effective GenAI solutions tailored to client needs.
- Apply GenAI Principles – Utilize modern tools and frameworks like LangGraph, to build scalable, reliable, and maintainable Compound AI systems.
- Leverage your understanding of AI fundamentals to ensure every project meets rigorous industry and ethical standards.
- Adapt to the latest Technologies & Patterns – continue to research, learn, and stay abreast of the most recent state of the art for AI application development.
- Promote Knowledge Sharing –Bolster our culture of continuous learning by sharing knowledge about AI engineering best practices through blog posts, articles, and internal talks.
Requirements:
- 2+ years of experience in AI engineering, machine learning (ML), or related fields
- Strong understanding of state of the art techniques in generative AI, including large language models (LLMs), text generation and other foundation models
- Familiarity with AI orchestration tools (e.g. LangGraph, CrewAI, Bedrock Agents, smolagents, etc)
- Experience in fine-tuning, prompt engineering or otherwise adapting generative models for specific use cases
- Experience with AI model evaluation, including human-in-the-loop and LLM judge paradigms
- Familiarity with NLP libraries and frameworks
- Hands-on experience in implementing Retrieval Augmented Generation (RAG) architectures and integrating retrieval systems with generative models
- Knowledge of at least one vector store or database (e.g. Opensearch, Pinecone, PostgreSQL with pgvector) and techniques for similarity search
- Familiarity with common data ingestion/ETL patterns for populating knowledge bases
- Experience with implementing LLM tool calling (either directly, via an orchestration framework, or using Model Context Protocol (MCP) clients)
- Experience using Amazon Bedrock or Databricks Mosaic AI for deploying and managing generative AI models
- Strong programming skills in Python (or similar languages)
- Familiarity with CI/CD pipelines and MLOps practices to ensure seamless integration, testing and deployment of AI models
Benefits:
- Competitive salary
- Flexible working hours
- Professional development budget
- Home office setup allowance
- Global team events
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