Rearc

AI Application Engineer

Rearc

full-time

Posted on:

Location Type: Remote

Location: India

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About the role

  • 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
Applicant Tracking System Keywords

Tip: use these terms in your resume and cover letter to boost ATS matches.

Hard Skills & Tools
AI engineeringmachine learninggenerative AIlarge language modelstext generationfine-tuningprompt engineeringNLP librariesRetrieval Augmented Generationprogramming in Python
Soft Skills
collaborationknowledge sharingcontinuous learning