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This role is for one of our client companies — a VC-backed AI native B2B saas startup that has raised $5.5M USD in funding.

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Apply once and, if selected, get access to up to 20 remote and onsite interview opportunities.

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CodeRound AI matches the top 5% tech talent with the fastest-growing, VC-funded AI startups across Silicon Valley and India.

Top-tier product startups across the US, UK, EU, UAE, and India have hired top engineers through CodeRound.

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We are looking for an Applied AI Engineer to design and scale production-grade RAG pipelines and intelligent agentic workflows. In this role, you will take advanced AI solutions from experimentation to production to solve complex enterprise problems.

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- Design, build, and own end-to-end RAG pipelines, covering document ingestion, preprocessing, chunking, embeddings, retrieval, reranking, and response generation.
- Develop and optimize retrieval architectures to improve relevance, factual accuracy, contextual understanding, and the quality of generated responses.
- Build robust evaluation frameworks by defining quality metrics, creating evaluation datasets, developing automated eval harnesses, and tracking system performance over time.
- Design and implement agentic workflows involving multi-step reasoning, tool use, orchestration, model selection, and context management.
- Continuously evaluate and improve LLM outputs through experimentation, error analysis, prompt optimization, retrieval tuning, and systematic benchmarking.
- Optimize AI pipelines for production requirements,



balancing response quality, latency, scalability, reliability, and computational costs.
- Collaborate with backend engineers to integrate and serve NLP outputs through reliable, scalable APIs that meet production performance requirements.
- Work with enterprise data from multiple sources, transforming unstructured and heterogeneous information into accurate, contextual intelligence for downstream workflows.

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- 3–6 years of experience in production NLP, Machine Learning, or Applied AI, with a track record of shipping models or pipelines used by real users.
- Hands-on experience designing, building, and optimizing production-grade Retrieval-Augmented Generation (RAG) pipelines, including retrieval architecture, chunking, reranking, and prompt design.
- Solid understanding of LLMs, NLP, semantic search, embeddings, context management, and retrieval-based systems.
- Experience defining quality metrics, building evaluation frameworks, developing evaluation harnesses, and systematically measuring LLM output quality.
- Strong Python engineering skills, including writing clean, maintainable, tested, production-grade code beyond experimentation in notebooks.
- Practical experience integrating LLMs such as OpenAI GPT models or Anthropic Claude into production applications.

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- Own your projects and build high-impact AI systems from scratch.
- Deploy scalable B2B solutions directly to global enterprise clients daily.
- Scale your career rapidly alongside elite engineers in a funded startup.
- Work in person with an ambitious team in our Mumbai hub.

📌 Applied AI Engineer (India)
🏢 CodeRound AI
📍 India