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Office in India: Chennai, India: Coimbatore
AI Solution Engineering& 23 others
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We're looking for a seasoned Lead AI Engineer to spearhead innovative AI and machine learning initiatives, guiding the development and rollout of state-of-the-art generative AI applications. This position gives you the chance to take charge of driving AI-powered efficiencies and meaningful business results while working alongside varied teams throughout the organization.
Responsibilities
- Construct and launch scalable AI/ML models and GenAI-based solutions into live production environments
- Build and sustain dependable ETL pipelines and data workflow processes
- Create applications powered by LLMs using contemporary development frameworks
- Apply prompt engineering strategies to maximize the quality of AI-generated outputs
- Roll out models through APIs and connect them with enterprise-level applications
- Take complete ownership across the lifecycle, covering development, deployment, tracking, and refinement
- Team up with cross-functional groups to produce AI solutions aligned with business goals
Requirements
- Between 8 and 13 years of broad IT experience
- More than 8 years specifically focused on AI Engineering
- At least 1 year of relevant experience in a leadership role
- Solid programming ability in Python
- Direct experience building ETL processes and data pipelines
- Strong background in ML/DL frameworks, such as TensorFlow, PyTorch, and Scikit-learn
- Working knowledge of prompt engineering practices and hands-on LLM experience
- Familiarity with LLM-focused frameworks like LangChain, LlamaIndex, and Hugging Face
- Practical experience with cloud platforms such as Azure, AWS, or GCP
- Capability using MLOps tooling, including MLflow, Kubeflow, and Airflow
- Solid background in API development and deploying models into production
- English proficiency at a B2 level or higher, with particular strength in technical communication
Nice to have
- Background working with RAG architectures and vector database technology
- Familiarity with real-time or streaming data pipeline design
- Exposure to designing scalable systems and microservices-based architecture
- Demonstrated skill with Databricks and PySpark
- Experience with cloud-based data solutions and ETL pipeline development