Architect / Principal, AI ML Engineer
New
United StatesFull-TimePrincipal
Salary not disclosed
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Job Details
- Experience
- 15+ years
- Required Skills
- PythonKubernetesPyTorchTensorflowLLMMLOpsGenerative AI
Requirements
- 15+ years of industry experience in AI, machine learning, or data science, ideally within IT services or enterprise environments.
- Master’s degree in Computer Science, Engineering, Mathematics, or related field (PhD preferred).
- Deep expertise in AI architecture patterns, including RAG systems, Agentic AI, MCP-based systems, and prompt orchestration.
- Strong hands-on experience with Python and ML frameworks such as PyTorch, TensorFlow, scikit-learn, and XGBoost.
- Proven experience working with Generative AI APIs (OpenAI, Claude, Gemini), including prompt engineering, embeddings, and fine-tuning techniques.
- Strong background in designing enterprise-scale ML systems with MLOps tools such as MLflow, Kubeflow, or SageMaker Pipelines.
- Familiarity with modern software engineering practices, including APIs, microservices, Docker, and Kubernetes.
- Experience in data governance, model risk management, compliance, and responsible AI principles.
- Strong leadership and communication skills, with the ability to influence technical and non-technical stakeholders.
- Demonstrated ability to drive innovation, define AI strategy, and guide complex technical transformations.
- Exposure to large-scale data systems and AI integration into production software products.
Responsibilities
- Define and lead end-to-end architecture for AI/ML, Generative AI, Agentic AI, and MCP-based systems, including data pipelines, model training/inference workflows, and scalable MLOps platforms.
- Act as a strategic advisor in client engagements, leading architecture discussions, presenting AI/ML solutions, and translating business problems into technical AI strategies.
- Design and implement scalable cloud-native AI solutions using platforms such as Azure ML, AWS SageMaker, or GCP Vertex AI.
- Lead the integration of Generative AI capabilities into enterprise applications using LLM APIs (OpenAI, Gemini, Claude) and open-source models such as LLaMA.
- Architect Retrieval-Augmented Generation (RAG) systems leveraging vector databases such as Pinecone, Weaviate, and FAISS.
- Guide MLOps practices, including CI/CD for ML, model versioning, monitoring, governance, and automated retraining pipelines.
- Evaluate emerging AI technologies, conduct build-vs-buy analysis, and define adoption strategies aligned with business and technical objectives.
- Mentor engineering teams and solution architects while promoting best practices in AI system design, responsible AI, and governance.
- Collaborate with leadership and stakeholders to align AI/ML strategy with broader organizational goals and innovation roadmaps.
- Represent the organization at industry events, conferences, and workshops as a subject matter expert in AI/ML.
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