Senior Generative AI

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Role Overview
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We are looking for a highly skilled Senior Generative AI & Backend Engineer to design, build, and scale AI -powered backend systems. The ideal candidate will have strong hands -on experience with Large Language Models (LLMs), Retrieval -Augmented Generation (RAG), and modern Python backend frameworks, along with the ability to deploy production -grade, secure, and scalable AI solutions.
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Key Responsibilities
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Generative AI Development
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• Develop, integrate, and optimize generative AI solutions using frameworks such as LangChain, Llama -Index, or similar tools.
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• Apply advanced prompt engineering techniques to design effective prompts and ensure high -quality LLM responses across diverse use cases.
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• Optimize LLM performance through prompt tuning, hyperparameter adjustments, response caching, and evaluation strategies.
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• Design and implement Retrieval -Augmented Generation (RAG) pipelines using vector databases such as Pinecone, Weaviate, Supabase, or PGVector.
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• Work with embeddings and similarity search techniques to build personalized and context -aware AI solutions.
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• Develop and support multimodal AI workflows, including text, image, and video understanding or generation.
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• Integrate observability and monitoring tools to track LLM performance, quality, latency, and reliability in production environments.
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  Backend Engineering
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  • Design, develop, and maintain scalable backend services using Python frameworks such as FastAPI, Django, or Flask.
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  • Build and maintain RESTful APIs for seamless integration between AI services and external systems.
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  • Optimize and manage relational databases (PostgreSQL, MySQL) alongside vector databases for AI -driven workflows.
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  • Implement asynchronous programming patterns to support high -concurrency and low -latency systems.
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  • Integrate third -party SDKs, APIs, and services while ensuring reliability and fault tolerance.
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  • Develop backend pipelines to handle multimodal data processing, including text, images, and video.
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  • Manage background jobs and scheduled tasks using Celery, cron jobs, or equivalent queueing systems.
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  • Use Docker and containerization best practices for reproducible and scalable deployments.
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  • Ensure backend systems are secure, scalable, and production -ready, following industry best practices.
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    Required Qualifications (Essential)
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    • 5–8 years of experience in backend development, with strong proficiency in Python.
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    • Hands -on experience with FastAPI, Django, or Flask.
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    • Solid understanding of Generative AI, including LLMs, embeddings, prompt engineering, and RAG architectures.
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    • Experience working with vector databases such as Pinecone, Weaviate, Supabase, or PGVector.
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    • Strong knowledge of relational databases (PostgreSQL, MySQL).
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    • Experience deploying AI solutions to production environments using Docker.
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    • Proficiency in asynchronous programming, background task processing, and concurrent systems.
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    • Strong testing and debugging skills, including unit and integration testing (e.g., Pytest).
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    • Ability to troubleshoot performance bottlenecks and optimize system reliability.
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       Preferred Qualifications
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      • Experience with cloud platforms such as AWS, GCP, or Azure (VMs, containers, or serverless services).
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      • Basic understanding of frontend technologies (HTML, CSS, JavaScript; React or Angular is a plus).
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      • Experience with observability, logging, and monitoring tools for backend and LLM systems.
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      • Familiarity with multimodal AI, agentic workflows, and emerging generative AI trends.
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      • Knowledge of secure coding practices, API security, and backend system hardening.
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      • Relevant certifications in AI, machine learning, or cloud technologies are a plus.
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