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Altimetrik - Generative AI Engineer

Altimetrik
5 - 11 Years
Multiple Locations

Posted on: 21/08/2026

Job Description

As a Gen AI Engineer, you will be at the forefront of designing and deploying advanced artificial intelligence solutions that solve complex business challenges. You will work closely with cross-functional teams, including data scientists, product managers, and enterprise architects, to integrate Large Language Models and generative frameworks into production-grade environments. Your work will directly influence how our clients leverage data-driven insights, ensuring that our AI implementations are not only innovative but also scalable, secure, and highly impactful for end-users.


Key Responsibilities :

- Architect and implement robust Generative AI pipelines to automate complex workflows and enhance decision-making processes for enterprise clients.

- Develop and fine-tune Large Language Models (LLMs) to ensure high performance and domain-specific accuracy across various business applications.

- Build and optimize Retrieval-Augmented Generation (RAG) systems to improve the relevance and context-awareness of AI-generated outputs.

- Manage the end-to-end lifecycle of machine learning models, from data ingestion and preprocessing to deployment and continuous monitoring.

- Collaborate with engineering teams to containerize and orchestrate AI services using Docker and Kubernetes, ensuring seamless integration into existing cloud infrastructures.

- Evaluate and integrate Vector Databases to facilitate efficient information retrieval and long-term memory capabilities for AI agents.


Required Skillset :

- Demonstrated expertise in Python and deep learning frameworks such as PyTorch and TensorFlow to build and scale sophisticated AI models.

- Proven ability to design and maintain RAG architectures and interact with VectorDBs to support high-performance search and retrieval tasks.

- Strong understanding of LLM orchestration and the ability to translate business requirements into technical AI specifications.

- Proficiency in containerization and orchestration tools including Docker and Kubernetes to ensure reliable model deployment in production environments.

- Excellent communication skills with the ability to articulate complex technical concepts to non-technical stakeholders and cross-functional partners.

- A minimum of 5 to 11 years of professional experience in machine learning and AI engineering, with a track record of delivering production-ready solutions.

- Ability to thrive in a collaborative, hybrid work environment across our Chennai, Bangalore, or Pune offices, maintaining high standards of engineering rigor and agility.

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