Full Time Role Hiring AI Architect Onsite Role in Jersey City, NJ

Key Responsibilities

• Define the enterprise AI architecture, frameworks, and roadmap aligned with business strategy.
• Architect end-to-end AI/ML systems, including data pipelines, model training, deployment, monitoring, and governance.
• Evaluate and select AI platforms, model types, and cloud-native technologies.
• Design scalable architectures for predictive analytics, NLP, computer vision, generative AI, and LLM-based applications.
• Lead PoCs, prototypes, and MVPs to validate feasibility and performance of AI solutions.
• Partner with engineering teams to ensure robust and secure deployment of AI pipelines.
• Oversee data ingestion, transformation, feature engineering, and data quality processes.
• Implement MLOps practices: CI/CD, automated model training, testing, deployment, and monitoring.
• Work with tools like MLflow, Kubeflow, Airflow, SageMaker, Vertex AI, Databricks, or Azure ML.
• Establish model governance, versioning, drift detection, explainability (XAI), and ethical AI guidelines.
• Ensure compliance with security, privacy, and regulatory standards (GDPR, ISO, SOC, etc.).
• Define risk assessment and model evaluation frameworks.
• Work with Product, Business, and Engineering teams to identify AI opportunities.
• Translate business use cases into technical AI solutions and architectural blueprints.
• Communicate complex AI concepts to non-technical stakeholders.
• Optimize model performance, inference latency, cost efficiency, and system reliability.
• Implement distributed model training and large-scale data processing pipelines.
• Ensure architectures support high-volume, real-time, or near-real-time AI workloads.
• Stay updated on latest AI advancements: foundation models, LLMs, agents, vector databases, and multimodal AI.
• Drive adoption of generative AI frameworks (LangChain, LlamaIndex, RAG, fine-tuning).
• Provide technical mentorship to data scientists and ML engineers.

Required Skills & Qualifications

• Bachelor's or Master's in Computer Science, AI/ML, Data Science, or related field.
• 7+ years of experience in ML/AI engineering, ML architecture, or data engineering.
• Strong knowledge of ML algorithms, deep learning, NLP, LLMs, reinforcement learning, and generative AI.
• Proficiency in Python, SQL, and frameworks like TensorFlow, PyTorch, Scikit-Learn, Hugging Face.
• Expertise in cloud platforms: AWS, Azure, or GCP.
• Hands-on experience with MLOps tools and pipelines.
• Ability to design secure, scalable, and distributed AI systems.
• Excellent communication and leadership skills.