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Posted:4 days ago| Platform: Linkedin logo

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Full Time

Job Description

Key Responsibilities:


• Design, develop, and deploy LLM-powered AI assistants utilizing OpenAI, Llama, Gemini,

or custom fine-tuned models to enhance conversational AI capabilities.

• Implement Retrieval-Augmented Generation (RAG) to seamlessly integrate enterprise

knowledge into GPT-based responses, ensuring accuracy and contextual relevance.

• Collaborate with architects to optimize scalable APIs, vector databases, and cloud-native

architectures, ensuring efficient AI model deployment and integration.

• Develop robust AI pipelines using LangChain, Hugging Face, and OpenAI SDKs to

streamline AI workflows and enhance model performance.

• Deploy AI-driven applications on Google Cloud Platform (GCP), leveraging Vertex AI,

BigQuery ML, Cloud Functions, Kubernetes, and Docker for scalability and reliability.

• Ensure high code quality, security, and performance by implementing best practices in

DevOps and MLOps, maintaining efficiency across AI development lifecycles.

• Implement and maintain robust CI/CD pipelines to ensure efficient and reliable software

delivery (e.g. automated build, test, and deployment processes)


WHO ARE WE LOOKING FOR:


• Experience: Minimum 4+ years in AI development, with at least 2+ year of hands-on

experience in Generative AI for Natural Language Processing (NLP) or Computer Vision.

• Technical Expertise: Strong proficiency in LangChain, Hugging Face, Transformers, or

Generative AI frameworks to build and optimize AI models.

• Programming Skills: Expertise in Python (mandatory), with optional experience in Node.js

or C++.

• Cloud Proficiency: Hands-on experience with Google Cloud Platform (GCP) (preferred) or

other cloud platforms like AWS or Azure.

• Database & API Experience: Strong knowledge of REST APIs, SQL/NoSQL databases, and

vector databases for scalable AI applications.

• DevOps & MLOps: Practical experience in CI/CD, DevOps, and microservices architectures,

including tools like Docker, Kubernetes, GitHub Actions, and Jenkins.

• Soft Skills: Demonstrated ownership, collaboration, and adaptability in a dynamic, fastpaced

work environment.

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