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AI Architect

AI Architect

Ally-eXecutive HRsangli, India
1 day ago
Job description

We are looking for Architects with exp in AI, ML / DL. Min 2 years in architecture to 6 years is required.

Key Responsibilities :

  • Worked on the AI / ML architecture roadmap aligned with organizational strategy, ensuring scalability, reliability, and security.
  • Architect and develop AI solutions : data pipelines, model development, deployment, monitoring, and governance.
  • Develop and Lead the implementation of MLOps frameworks for CI / CD, model registry, reproducibility, drift detection, and lifecycle management.
  • Evaluate and select suitable AI / ML frameworks, tools, and cloud platforms; ensure optimal use of technologies.
  • Partner with data engineering, product, and business teams to identify opportunities for AI adoption and design scalable solutions.
  • Provide technical leadership and mentorship to ML engineers, data scientists, and developers.
  • Ensure compliance with data security, ethical AI, and regulatory standards in AI system design.
  • Drive innovation by staying updated on emerging AI research, trends, and best practices.

Required Skills & Qualifications

  • 6–10 years of relevant experience in AI / ML engineering, data science, or AI solution architecture.
  • Strong proficiency in Python (preferred) and familiarity with enterprise-grade programming practices.
  • Deep expertise in ML / DL frameworks : TensorFlow, PyTorch, scikit-learn.
  • Proven experience in architecting and deploying AI solutions on cloud platforms (AWS SageMaker, GCP Vertex AI, Azure ML).
  • Solid understanding of data engineering, distributed systems, and API / microservices-based architectures.
  • Knowledge of big data tools (Spark, Kafka, Hadoop) and data pipeline orchestration.
  • Strong grounding in statistics, probability, linear algebra, optimization, and algorithm design.
  • Experience designing systems with observability, fault tolerance, scalability, and cost-efficiency.
  • Bachelor’s or Master’s degree in Computer Science, Engineering or related field.
  • Preferred Qualifications :

  • Experience with enterprise AI governance frameworks, including model explainability and responsible AI.
  • Hands-on expertise with containerization (Docker, Kubernetes) and distributed model training.
  • Contributions to open-source AI projects, patents, or publications in applied AI / ML.
  • Familiarity with GenAI (LLMs, transformers, prompt engineering) and applied use cases in enterprises.
  • Soft Skills & Qualities

    ∙Strategic thinker with the ability to connect business goals with AI capabilities.

    ∙Strong development and mentoring skills; able to guide cross-functional teams.

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