Principal Artificial Intelligence Engineer - Generative AI/LLM (8-12 yrs)

Posting title : Principal AI Engineer

Experience : 8+ Years

Location : Bangalore

Work mode : Hybrid

Primary skills : Python, TensorFlow, PyTorch, LangChain, CrewAI, AutoGen, OpenAI, Hugging Face, MLOps, and Cloud AI- AWS/Azure/GCP

Qualification : Any Engineering/ Computers degree

Key Responsibilities :

AI Research & Implementation :

- Read, interpret, and implement state-of-the-art AI/ML white papers into practical, high-impact solutions.

- Stay updated with the latest advancements in AI, particularly in agentic AI, LLMs, and GenAI applications.

Agentic AI Development :

- Design and build agentic AI applications that can autonomously perform tasks, make decisions, and improve workflows.

- Work with multi-agent systems, memory architectures, reasoning engines, and integration with external tools.

Complex Problem Solving in BFSI :

- Solve highly complex problems in BFSI, such as risk assessment, fraud detection, credit scoring, and compliance automation.

- Develop AI models that optimize decision-making and efficiency in financial services.

End-to-End AI System Development :

- Architect, train, and deploy scalable AI/ML models and pipelines.

- Optimize models for performance, interpretability, and compliance.

Leadership & Collaboration :

- Provide technical mentorship to engineers and data scientists.

- Collaborate with cross-functional teams including product managers, business stakeholders, and engineers.

Experimentation & Prototyping :

- Rapidly prototype AI solutions using Python, TensorFlow, PyTorch, LangChain, LlamaIndex, etc.

- Optimize AI workflows with retrieval-augmented generation (RAG), fine-tuned LLMs, and vector databases.

Required Skills & Experience :

- 8+ years of experience in AI/ML engineering, with a strong research and development background.

- Expertise in agentic AI frameworks (LangChain, CrewAI, AutoGen, OpenAI agents, etc.).

- Hands-on experience in building autonomous AI applications that interact with tools, APIs, and environments.

- Strong experience in LLMs, transformers, embeddings, RAG, and fine-tuning foundation models.

- Deep understanding of multi-modal AI, reinforcement learning, and probabilistic modeling.

- Proven track record of implementing AI/ML research papers into production.

- BFSI domain expertise - experience in financial risk modeling, fraud detection, predictive analytics, etc.

- Proficiency in Python, PyTorch, TensorFlow, Hugging Face, OpenAI API, LangChain, and cloud AI services (AWS/GCP/Azure).

- Experience with MLOps, data pipelines, and vector databases (Pinecone, Weaviate, ChromaDB, FAISS).

Preferred Qualifications :

- Publications or patents in AI/ML research.

- Experience in knowledge graphs, reasoning systems, and symbolic AI.

- Contributions to open-source AI projects.

- Background in quantitative finance, computational statistics, or AI in financial markets.