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Job Description

Job Description :


Key Responsibilities :


- Lead the implementation and delivery of AI and Generative AI applications.


- Design end-to-end AI systems using commercial and open-source tools.


- Translate business requirements into scalable AI-driven solutions.


- Collaborate with data engineering teams to ensure data quality, governance, and smooth data flows.


- Define reference architectures, technical roadmaps, and best practices for AI applications.


- Design and manage data ingestion pipelines, model training environments, CI/CD, and monitoring systems.


- Use containerization and cloud services to deploy and scale AI systems.


- Ensure scalability, reliability, security, and maintainability of AI solutions.


- Provide technical mentorship and conduct knowledge-sharing sessions.


Requirements :


- 5+ years of experience in AI, Machine Learning, or related roles.


- Strong experience building AI agents using LangGraph, AutoGen, or CrewAI.


- Proficiency in Python and ML/DL frameworks such as TensorFlow, PyTorch, Keras.


- Solid understanding of Deep Learning and NLP (RNN, CNN, LSTM, Transformers).


- Experience with cloud platforms (AWS, Azure, or GCP) for AI deployments.


- Strong knowledge of distributed systems, REST APIs, GraphQL, and microservices.


- Familiarity with event-driven architectures and message brokers (Kafka, RabbitMQ).


Good to Have :


- Experience with Docker, Kubernetes, and CI/CD tools (Jenkins, GitLab).


- Knowledge of SQL and NoSQL databases (PostgreSQL, MongoDB, Cassandra).


- Experience with Infrastructure as Code (Terraform, CloudFormation).


- Hands-on exposure to Hugging Face, OpenAI APIs, and other LLM tools.


- Experience with MLOps / LLMOps, model training, and fine-tuning (GPT-4, LLaMA, PaLM).


- Familiarity with monitoring and logging tools (Prometheus, Grafana, ELK).

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