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Salary
≈ $21k – $43k per year (Estimated)
Location
In office (Gurgaon)
Seniority
Senior · 5+ years exp

First seen by Alion on Oct 7, 2026.

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Incedo is a digital engineering and data science services firm. Its teams build machine learning and analytics platforms for clients. The company works across financial services, telecom and life sciences.

Job Description :


As a Senior Generative AI & NLP Developer at Incedo, you will take ownership of designing and developing production-grade NLP and GenAI solutions.

You will work across the complete AI application lifecycle - from understanding business requirements and designing solution architectures to implementation, optimization, deployment, and production support.

You will be expected to independently solve complex problems involving LLMs, RAG, NLP pipelines, information retrieval, embeddings, and document intelligence, while also providing technical guidance to other developers.

Key Responsibilities :

- Design and develop end-to-end LLM and NLP applications for enterprise use cases such as knowledge assistants, document intelligence, conversational AI, summarization, information extraction, and semantic search.

- Architect and implement robust RAG pipelines, including document ingestion, parsing, chunking, embedding, indexing, retrieval, reranking, and context construction.

- Evaluate and select appropriate LLMs, embedding models, retrieval strategies, and NLP techniques based on business and technical requirements.

- Develop scalable Python services and APIs using FastAPI/Flask and integrate AI capabilities with enterprise applications.

- Work extensively with Hugging Face Transformers, LangChain, LlamaIndex, SpaCy, and related AI/NLP ecosystems.

- Design and optimize vector-search solutions using FAISS, Pinecone, Weaviate, Milvus, or equivalent technologies.

- Implement prompt engineering, structured generation, function/tool calling, grounding, and LLM evaluation strategies.

- Analyze model and application performance and improve latency, accuracy, relevance, scalability, and cost efficiency.

- Develop evaluation frameworks and metrics for assessing retrieval quality, response quality, hallucination, and overall RAG performance.

- Lead integration of GenAI applications with existing enterprise systems, APIs, and data platforms.

- Review code and architecture, establish development standards, and mentor junior developers.

- Troubleshoot complex production issues and drive root-cause analysis and resolution.

- Collaborate with architects, product managers, data scientists, and engineering teams to translate requirements into technical solutions.

- Contribute to technical design documents, proof-of-concepts, and solution proposals.

Required Skills :

- Strong Python expertise, including OOP, asynchronous/concurrent programming, API development, data structures, and performance optimization.

- Strong hands-on experience building production-grade NLP/GenAI applications.

- Deep understanding of LLMs, prompt engineering, embeddings, RAG, semantic search, and information retrieval.

- Strong experience with Hugging Face Transformers, LangChain, LlamaIndex, or comparable frameworks.

- Experience designing and implementing vector-search solutions using FAISS, Pinecone, Weaviate, Milvus, or equivalent.

- Strong experience with text extraction, preprocessing, document processing, and NLP pipelines.

- Experience developing APIs and microservices using FastAPI/Flask.

- Strong understanding of LLM evaluation, retrieval optimization, and response-quality improvement.

- Proficiency with Pandas/NumPy and experience handling real-world datasets.

- Strong understanding of software engineering, Git, testing, CI/CD, and production deployment practices.

Skills

Generative AI, NLP, Artificial Intelligence, Python, RAG, Machine Learning, Deep Learning, Numpy, Pandas

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