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Open nowFirst seen 40 hours ago

AI Engineer- Anthropic

Quantum Strides LLC168 open roles

Where
Chennai, Tamil Nadu, India, Remote
Work mode
Remote
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Your applicationOpen nowAI Engineer- AnthropicQuantum Strides LLC · Chennai, Tamil Nadu, India, Remote

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  2. CV RocketCV written for this posting.

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The clock on this job

Early applications get read.

11.8% of postings close within 7 days. Measured by our own scanner across the market.

Share of postings closed within
  1. 2.1%1 day
  2. 4.4%3 days
  3. 11.8%7 days
  4. 18.6%14 days
  5. 35.6%30 days
  6. 45.1%60 days
This job: first seen 40 hours ago

The posting

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/TypeScript is a plus.
  • Experience working with REST APIs, JSON, databases, and third-party integrations.
  • Familiarity with AI/ML frameworks such as LangChain, LlamaIndex, 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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