GenAI Automation developer

1 day ago

Clinton, NJ, United States E-Solutions Full time

Title: GenAI Automation developer

Location: Iselin, NJ (Hybrid role 3 days a week onsite) need local candidates

JD:

GenAI Automation Technical Leadership: Lead the design and architecture of GenAI-powered automation systems across multiple domains. Mentor and guide junior engineers and data scientists in best practices for GenAI development and deployment. Drive technical decision-making, ensuring alignment with business goals and AI ethics. Establish coding standards, model evaluation protocols, and CI/CD pipelines for GenAI workflows. Collaborate with product managers, stakeholders, and cross-functional teams to define technical roadmaps and deliverables. Evaluate emerging GenAI technologies and recommend adoption strategies. Engineering & Automation: Build and deploy automation solutions using LLMs and GenAI platforms (e.g., OpenAI, Hugging Face, Azure OpenAI). Develop APIs, microservices, and integration layers to embed GenAI into enterprise systems. Fine-tune and optimize models for tasks like summarization, document generation, code synthesis, and conversational AI. Monitor model performance, manage drift, and implement feedback loops for continuous improvement. Ensure compliance with data governance, security, and responsible AI standards. Required Qualifications: Bachelors or Masters degree in Computer Science, Engineering, or related field. experience in software engineering, with in AI/ML or automation. Proven experience leading technical teams or projects in AI/ML or automation domains. Strong proficiency in Python, cloud platforms (AWS, Azure, GCP), and ML frameworks (PyTorch, TensorFlow). Deep understanding of LLMs, NLP, and GenAI model lifecycle. Excellent communication and stakeholder management skills. Preferred Qualifications: Experience with RPA tools (e.g., UiPath, Automation Anywhere). Knowledge of MLOps, prompt engineering, and model fine-tuning. Familiarity with enterprise architecture and scalable AI deployment strategies. Contributions to open-source AI projects or technical publications.

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