Talenthub

Hire remote software engineers for custom development

GenAI Engineer

Experience: 5+ Years
Location: Remote / Hybrid / Onsite (as applicable)
Duration: Full-time / Contract

Job Summary :

We are seeking an experienced GenAI Engineer to design, develop, and deploy advanced Generative AI solutions using state-of-the-art large language models (LLMs) and AI frameworks. The ideal candidate will have strong expertise in machine learning, prompt engineering, NLP, and cloud-based AI services, with hands-on experience integrating AI models into enterprise applications.

Key Responsibilities :

  • Design and develop Generative AI applications leveraging LLMs (e.g., GPT, Claude, Gemini, Llama) and related frameworks.
  • Build, fine-tune, and deploy custom AI models for text generation, summarization, chatbots, and automation tasks.
  • Develop and maintain end-to-end AI pipelines, from data ingestion to model deployment.
  • Implement prompt engineering and retrieval-augmented generation (RAG) techniques for improved model performance.
  • Integrate AI/ML models into web applications, APIs, and business systems using Python, Node.js, or similar technologies.
  • Utilize vector databases (e.g., Pinecone, FAISS, Weaviate) and embedding models for semantic search and contextual retrieval.
  • Collaborate with cross-functional teams to identify AI-driven solutions that enhance productivity and decision-making.
  • Deploy and manage AI workloads on cloud platforms (Azure OpenAI, AWS Bedrock, Google Vertex AI, etc.).
  • Ensure model governance, data privacy, and compliance with enterprise security standards.
  • Stay updated with advancements in GenAI tools, frameworks, and model architectures.

Required Skills :

  • 5+ years of hands-on experience in AI/ML engineering with at least 2 years in Generative AI.
  • Strong programming skills in Python, with experience in frameworks such as LangChain, LlamaIndex, Hugging Face Transformers, or OpenAI API.
  • Experience with cloud AI services (Azure OpenAI, AWS Sagemaker/Bedrock, Google Vertex AI).
  • Solid understanding of LLMs, embeddings, RAG architecture, and vector databases.
  • Familiarity with containerization and orchestration tools (Docker, Kubernetes).
  • Experience integrating AI into enterprise-grade web or SaaS applications.
  • Good understanding of MLOps, CI/CD for ML, and versioning of models and data.

Nice to Have :

  • Experience building custom agents or autonomous AI workflows.
  • Knowledge of data labeling, model evaluation, and bias mitigation techniques.
  • Exposure to front-end frameworks (React, Next.js) for building AI-powered interfaces.
  • Experience with API security, monitoring, and scaling AI services.
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