Python GenAI Engineer

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We are looking for a highly skilled Senior Generative AI / Backend Engineer<\/b> with strong experience in building AI -powered applications and scalable backend systems. The ideal candidate will have hands -on expertise in LLMs, Retrieval -Augmented Generation (RAG), prompt engineering<\/b>, and Python -based backend development<\/b>, with the ability to deliver production -ready AI solutions.
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Key Responsibilities<\/b>
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Generative AI Development<\/b>
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• Design, develop, and deploy generative AI solutions using frameworks such as LangChain<\/b> and LlamaIndex<\/b>.
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• Apply advanced prompt engineering<\/b> techniques to optimize LLM responses across multiple use cases.
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• Work with advanced LLM features including prompt optimization, hyperparameter tuning, and response caching<\/b>.
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• Implement Retrieval -Augmented Generation (RAG)<\/b> workflows by integrating vector databases such as Pinecone, Weaviate, Supabase, or PGVector<\/b>.
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• Develop solutions leveraging embeddings and similarity search<\/b> for intelligent and personalized query resolution.
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• Process and analyze multimodal data<\/b>, including text, images, and video for AI -driven applications.
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• Integrate observability and monitoring tools<\/b> to track LLM performance, reliability, and quality.
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  Backend Engineering<\/b>
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  • Build and maintain scalable, secure backend services using Python frameworks<\/b> such as FastAPI, Django, or Flask<\/b>.
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  • Design and implement RESTful APIs<\/b> for seamless system integration.
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  • Optimize and manage relational databases<\/b> (PostgreSQL, MySQL) and vector databases<\/b> for AI workflows.
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  • Implement asynchronous programming<\/b> patterns and follow clean coding best practices.
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  • Integrate third -party SDKs and APIs<\/b> to support external system interoperability.
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  • Develop backend pipelines for multimodal data processing<\/b> (text, image, and video).
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  • Manage background and scheduled tasks using Celery, cron jobs, or job queues<\/b>.
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  • Use Docker<\/b> for containerization and reproducible deployments.
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  • Ensure backend systems are secure, scalable, and production -ready<\/b>.
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    Qualifications<\/b>
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    Essential Skills<\/b>
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    • Strong proficiency in Python<\/b> and backend frameworks (FastAPI, Django, Flask<\/b>).
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    • Hands -on experience with Generative AI frameworks<\/b> such as LangChain, LlamaIndex<\/b>, and RAG architectures.
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    • Strong understanding of LLMs, embeddings, and similarity search<\/b> techniques.
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    • Experience with relational databases<\/b> (PostgreSQL, MySQL) and vector databases<\/b> (Pinecone, Weaviate, Supabase, PGVector).
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    • Experience deploying AI solutions to production using Docker<\/b>.
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    • Strong skills in testing, debugging, and performance optimization<\/b> (Pytest, unit/integration testing).
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    • Solid understanding of asynchronous programming<\/b> and concurrent task handling.
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      Preferred Skills<\/b>
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      • Experience with cloud platforms<\/b> such as AWS, GCP, or Azure<\/b>.
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      • Basic understanding of frontend technologies<\/b> (HTML, CSS, JavaScript; Angular or React is a plus).
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      • Experience with observability and monitoring tools<\/b> for real -time LLM evaluation.
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      • Awareness of emerging trends in generative AI, multimodal AI, and agent -based workflows<\/b>.
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      • Knowledge of secure coding practices<\/b> and backend system hardening.
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      • Relevant certifications<\/b> in AI, Machine Learning, or Cloud technologies are a plus.
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