Senior AI Architecture Lead

2 days ago

Noida, Uttar Pradesh, India beBeeSolution Full time ₹ 20,00,000 - ₹ 25,00,000
Job Description:The company is a fast-growing, US private equity–backed AI firm making significant headway in both the US and India markets. It delivers outcome-focused digital experiences—from mobile and web to cloud and AI—for enterprise clients worldwide.

Key Responsibilities:
  • Design and own the end-to-end architecture of intelligent systems including data ingestion (ETL/ELT), transformation, storage, modeling, inferencing, and reporting.
  • Architect GenAI-powered applications using LLMs, vector databases, and RAG pipelines; Agentic Workflow, integrate with enterprise knowledge graphs and document repositories.
  • Lead the design and deployment of agentic AI systems that can plan, reason, and interact autonomously within business workflows.
  • Collaborate with cross-functional teams including data scientists, data engineers, MLOps, and frontend/backend developers to deliver scalable and maintainable solutions.
  • Define patterns and best practices for traditional ML and GenAI projects, covering model governance, explainability, reusability, and lifecycle management.
  • Ensure seamless integration of ML/AI systems via RESTful APIs with frontend interfaces (e.g., dashboards, portals) and backend systems (e.g., CRMs, ERPs).
  • Architect multi-cloud or hybrid cloud AI solutions, leveraging services from AWS, Azure, or GCP for scalable compute, storage, orchestration, and deployment.
  • Provide technical oversight for data pipelines (batch and real-time), data lakes, and ETL frameworks ensuring secure and governed data movement.
  • Conduct architecture reviews, mentor engineering teams, and drive design standards for AI/ML, data engineering, and software integration.
Qualifications:
  • Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
  • 10+ years of experience in software architecture, including at least 4 years in AI/ML-focused roles.
Required Skills:
  • Expertise in machine learning (regression, classification, clustering), deep learning (CNNs, RNNs, transformers), and NLP.
  • Experience with Generative AI frameworks and services (e.g., OpenAI, LangChain, Azure OpenAI, Amazon Bedrock).
  • Strong hands-on Python skills, with experience in libraries such as Scikit-learn, Pandas, NumPy, TensorFlow, or PyTorch.
  • Proficiency in RESTful API development and integration with frontend components (React, Angular, or similar is a plus).
  • Deep experience in ETL/ELT processes using tools like Apache Airflow, Azure Data Factory, or AWS Glue.
  • Strong knowledge of cloud-native architecture and AI/ML services on either one of the cloud AWS, Azure, or GCP.
  • Experience with vector databases (e.g., Pinecone, FAISS, Weaviate) and semantic search patterns.
  • Experience in deploying and managing ML models with MLOps frameworks (MLflow, Kubeflow).
  • Understanding of microservices architecture, API gateways, and container orchestration (Docker, Kubernetes).

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