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AI Engineer- Anthropic

Job in Phoenix, Maricopa County, Arizona, 85001, USA
Listing for: Quantum Strides LLC
Full Time position Listed on 2026-11-05
Job specializations:
  • Software Development
    AI Engineer (Applied/Software), Machine Learning/ ML Engineer
Salary/Wage Range or Industry Benchmark: 9400 USD Monthly USD 9400.00 MONTH

Job Description & How to Apply Below

Location:

India

Job Description Artificial Intelligence Engineer - Anthropic About Quantum Strides

Quantum Strides is looking for a talented and hands-on Artificial Intelligence Engineer to join our growing AI engineering team. The ideal candidate will have strong practical experience building and deploying AI/ML solutions, with specific expertise in Anthropic's Claude ecosystem, APIs, and generative AI technologies
.

This is a fully remote, full-time opportunity for an engineer who enjoys working with emerging AI technologies and translating business requirements into scalable, production-ready AI solutions.

Key Responsibilities
  • Design, develop, and deploy AI-powered applications using Anthropic Claude and related AI technologies
    .
  • Build applications and workflows using Anthropic APIs/SDKs and modern Generative AI frameworks.
  • Develop LLM-powered applications, AI agents, conversational AI, and intelligent automation solutions
    .
  • Implement Retrieval-Augmented Generation (RAG) solutions using enterprise and unstructured data.
  • Develop effective prompting strategies, prompt templates, evaluation approaches, and LLM workflows.
  • Integrate AI models with enterprise applications, APIs, databases, and cloud platforms.
  • Work with vector databases and embedding technologies for semantic search and knowledge retrieval.
  • Develop and optimize AI agents capable of tool use, reasoning workflows, and multi-step task execution.
  • Evaluate AI model performance, accuracy, latency, reliability, and cost.
  • Implement appropriate guardrails, security controls, monitoring, and responsible AI practices.
  • Collaborate with product managers, software engineers, data engineers, and business stakeholders to deliver AI solutions.
  • Troubleshoot, optimize, and continuously improve AI applications in production environments.
  • Stay current with developments in Anthropic, Claude, Generative AI, LLMs, AI agents, and AI engineering best practices
    .
Required

Skills & Qualifications
  • 3-4 years of professional experience
    in Artificial Intelligence, Machine Learning, Generative AI, or related engineering roles.
  • Anthropic certification is required.
  • Hands-on experience with Anthropic Claude models and Anthropic APIs/SDKs
    .
  • Strong understanding of Generative AI and Large Language Models (LLMs).
  • Experience developing LLM-based applications, chatbots, AI assistants, or AI agents.
  • Strong knowledge of Prompt Engineering and LLM evaluation techniques.
  • Experience implementing RAG architectures
    , embeddings, vector search, and knowledge retrieval.
  • Programming experience in Python
    ; experience with JavaScript/Type Script is a plus.
  • Experience working with REST APIs, JSON, databases, and third-party integrations.
  • Familiarity with AI/ML frameworks such as Lang Chain, Llama Index, or comparable frameworks
    .
  • Experience with vector databases such as Pinecone, Weaviate, Milvus, Chroma, or similar technologies
    .
  • Understanding of cloud platforms such as AWS, Azure, or IBM Cloud
    .
  • Familiarity with Docker, Git, CI/CD, and production deployment practices.
  • Strong analytical, problem-solving, and communication skills.
Preferred Qualifications
  • Experience building AI agents and agentic workflows
    .
  • Experience with Claude tool use/function calling and enterprise AI integrations.
  • Experience with MCP (Model Context Protocol) or similar AI integration approaches.
  • Experience with model evaluation, observability, and AI application monitoring.
  • Knowledge of fine-tuning, model adaptation, embeddings, and NLP techniques.
  • Experience integrating AI solutions with enterprise systems and business applications.
  • Exposure to Responsible AI, AI security, privacy, and LLM governance.
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