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AI Engineer – GenAI / LLM / RAG | Python | LangChain
AI Engineer – GenAI / LLM / RAG | Python | LangChain
Apptware is seeking an AI Engineer with 4-6 years of experience to develop and deploy AI-driven systems, focusing on GenAI, LLMs, and scalable machine learning solutions. The role involves building GenAI/LLM applications, designing RAG pipelines, and developing embedding-based solutions for search and recommendations.
About the role
About Apptware
At Apptware, we are building AI-driven systems that solve complex, real-world business problems. We are looking for an AI Engineer who enjoys working with GenAI, LLMs, and scalable machine learning solutions.
Role: AI Engineer – GenAI / LLM / RAG | Python | LangChain
Experience: 4–6 years
Location: Pune or Bangalore
What you should bring
- Strong background in Computer Science, AI, Mathematics, Statistics, or a related quantitative field discipline
- Hands-on experience with Python and statistical libraries
- Strong fundamentals in probability, statistics, ML algorithms, and computer science
- Experience with ML techniques such as classification, regression, feature engineering, hyperparameter tuning, unsupervised learning, and time-series analysis
- Proven experience in training, fine-tuning, and deploying Generative AI models
- Hands-on experience with LLMs such as GPT, LLaMA, Mistral, Claude, or similar
- Experience building RAG pipelines using vector databases like Pinecone, Weaviate, Milvus, or FAISS
- Good understanding of embeddings and their use in semantic search and recommendations
- Exposure to agentic AI frameworks like LangChain, LlamaIndex, AutoGen, or CrewAI
- Experience with R, SAS, SPSS, Strata, or MATLAB is a plus
What you will work on
- Build and deploy GenAI and LLM-based applications, including chatbots, copilots, and agents
- Design and optimise RAG pipelines for enterprise knowledge systems
- Develop embedding-based solutions for search, personalisation, and recommendations
- Work with unstructured data to build scalable ML and AI solutions
- Design experiments, test hypotheses, and communicate insights clearly
Nice to have
- Experience with NLP techniques and libraries such as SpaCy, NLTK, Hugging Face, or OpenAI APIs
- Understanding of BERT, ELMo, LSTM, and CNN architectures
- Exposure to cloud AI platforms like AWS SageMaker or Azure Machine Learning
- Experience with multimodal AI or advanced ML techniques
- Personal projects or Kaggle experience