Posted:1 week ago|
Platform:
Work from Office
Full Time
Key Responsibilities:
Technical Leadership
Lead the design and implementation of AI-driven systems using Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and Agentic AI approaches.
Architect scalable, cloud-native solutions leveraging AWS services for AI and data workflows.
Build and optimize NLP pipelines for information extraction, summarization, semantic search, and conversational systems.
Develop, evaluate, and deploy AI models into production environments using modern MLOps best practices.
Collaborate with product and engineering teams to identify, scope, and deliver AI-driven features and solutions.
Hands-On Development
Write efficient, production-ready code in Python for AI model integration, APIs, and backend workflows.
Use SQL for data exploration, querying, and validation.
Implement RAG pipelines integrating LLMs with Vector Databases and retrieval systems.
Design and fine-tune LLMs for domain-specific applications.
Innovation & Research
Explore and apply cutting-edge techniques in Agentic AI, LLMs, and RAG to solve business challenges.
Stay up to date with advancements in generative AI, foundation models, and AI tooling.
Mentor junior team members and foster a culture of experimentation and continuous learning.
Requirements:Must Have Skills:
Python (strong proficiency in AI/ML and backend development)
RAG (Retrieval-Augmented Generation) – design and implementation experience
LLMs (Large Language Models) – fine-tuning, integration, and deployment
Agentic AI – building autonomous or semi-autonomous AI systems
NLP (Natural Language Processing) – model development and text analytics
SQL – database querying and data wrangling
AWS – cloud architecture, deployment, and scaling AI workloads
What We Offer:
Globallogic
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