Senior AI Engineer

persistent

Bengaluru, India 8 Years Exp Posted 60d ago

Design and implement ML and NLP models and pipelines
Perform data preprocessing, feature engineering, and model evaluation
Improve model accuracy, robustness, and efficiency
Build applications using Large Language Models (LLMs)
Develop and optimize prompts, embeddings, and inference workflows
Support fine-tuning and evaluation of LLM-based systems
Develop and maintain RAG pipelines integrating vector search and LLMs
Work with embedding models and vector databases such as Elastic, OpenSearch, and FAISS
Improve retrieval quality and response relevance
Contribute to building agent-based workflows and orchestration logic
Implement agent coordination and tool integrations
Work with frameworks like LangChain and Google ADK
Build scalable AI services and APIs
Develop real-time and batch inference solutions
Ensure code quality, performance optimization, and system reliability
Collaborate with engineers, product managers, and data scientists
Participate in design discussions and technical reviews
Contribute to documentation and knowledge sharing

Expertise You'll Bring:

5 to 7 years of software engineering experience
Minimum 3 years of experience in Machine Learning and NLP
1.5+ years of hands-on experience with LLM-based applications
Exposure to agent-based architectures or workflows
Strong understanding of NLP fundamentals (tokenization, embeddings, transformers)
Experience with ML frameworks like PyTorch or TensorFlow
Hands-on experience with LLMs such as GPT, Llama, Gemini, or Claude
Knowledge of prompt engineering and LLM evaluation techniques
Experience with frameworks like LangChain or Google ADK
Hands-on experience with RAG systems and vector databases
Understanding of semantic search and similarity search concepts
Strong programming skills in Python
Experience with REST APIs and microservices architecture
Knowledge of Docker and cloud platforms such as Azure, AWS, or GCP
Strong analytical and problem-solving skills
Exposure to agent workflows and tool-based reasoning systems
Experience with MLOps tools and pipelines
Knowledge of model monitoring and drift detection
Familiarity with LLM evaluation frameworks
Understanding of hybrid search or knowledge graph concepts