Posted on: 19/06/2026
About the Role :
We are looking for a GenAI Engineer with strong experience in building and delivering AI and Generative AI applications. The role involves designing end-to-end AI solutions, leading technical implementation, and mentoring teams while working closely with business and engineering stakeholders.
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- 12 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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