Senior AI Archtech
Senior AI Archtech
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Salary Not Disclosed
1 Vacancy
Job Description
We specialize in healthcare management technology and offer our clients a suite of utilization management software solutions. Our mission is to improve the quality of care and expedite the delivery of healthcare services by advancing and automating utilization management processes. We are based in Parsippany NJ and have clients across the United States. Key Responsibilities: Strategic AI Architecture
Design architect and oversee implementation of end-to-end AI systems spanning data ingestion model development evaluation deployment and observability.
Lead architecture for agentic systems with memory planning and tool-use capabilities.
Build hybrid AI architectures that integrate:
o Traditional ML (XGBoost SVM Random Forest)
o Deep Learning (CNNs RNNs Transformers)
o Generative AI (LLMs Diffusion Models Multimodal AI) Generative AI & Agentic Systems
Develop applications using LLMs (GPT-4/Claude/Gemini etc.) with frameworks like:
o LangChain LlamaIndex Haystack
o Vector DBs (Weaviate Pinecone FAISS Qdrant)
Architect RAG pipelines prompt engineering workflows and tool-using agents (AutoGPT-style).
Optimize inference memory management and token budgeting for agent runtimes. Traditional AI/ML & Data Science
Guide the development of supervised and unsupervised ML models for classification regression clustering forecasting and anomaly detection.
Translate business problems into mathematical formulations and data science models.
Collaborate with Data Engineering to optimize pipelines feature stores and model-serving infrastructure. Infrastructure & Tooling
Deploy models via cloud-native platforms (AWS Sagemaker Azure ML GCP Vertex AI).
Use MLOps tools for versioning CI/CD drift detection (MLflow Kubeflow Arize).
Leverage orchestration tools like Airflow or Prefect to manage complex workflows. Leadership & Governance
Mentor junior data scientists and AI engineers across the SDLC.
Participate in executive-level planning for AI adoption and roadmap.
Define and enforce responsible AI practices: model fairness privacy explainability. Qualifications: Required:
Bachelors or Masters in Computer Science AI Data Science or related field.
8 years experience in AI/ML with 3 years in architecture or leadership roles.
Proven delivery of AI systems in production: GenAI traditional ML.
Strong knowledge of LLMs Transformer models Vector embeddings and Agents.
Experience with Python (TensorFlow PyTorch HuggingFace Scikit-learn) SQL and cloud platforms. Preferred:
PhD in AI NLP or Applied ML.
Experience integrating AI into enterprise platforms decision support tools or clinical systems.
Familiarity with HIPAA GDPR or healthcare-specific data compliance (for regulated environments). Soft Skills & Traits:
Strategic thinker with strong communication skills.
Natural collaborator who can lead across data engineering product and executive
Employment Type
Full-time
