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Principal AI Engineer
Arting Digital
posted 2hr ago
Job Role Insights
Flexible timing
Key skills for the job
Job Description
Key Responsibilities:
- AI Research Implementation:
- 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).
Employment Type: Full Time, Permanent
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Flexible timing
Monday to Saturday
No travel
Day Shift
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