We are seeking a highly skilled and motivated AI Engineer with 5 to 8 years of experience to join our team. This role is a unique blend of deep technical expertise and strategic customer engagement. The ideal candidate will have a strong background in Python, Generative AI, and the end-to-end MLOps lifecycle.

As an AI Engineer, you will be responsible for designing, building, and deploying sophisticated AI solutions, with a focus on Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG). You will partner directly with business stakeholders and customers to understand their needs, translate them into technical requirements, and deliver robust, scalable AI applications that drive significant business impact.

Responsibilities:

- End-to-End Solution Development: Partner with internal and external stakeholders to lead the full lifecycle of AI projects from use case scoping and data exploration to model development, deployment, and performance optimization.
- Data-Centric AI Implementation: Champion a data-first approach to building AI applications. Design and implement scalable text processing pipelines, and establish best practices for data quality, including curating vector database collections, and developing tailored data chunking and vectorization strategies.
- Generative AI System Architecture: Architect and implement advanced AI systems utilizing contemporary orchestration frameworks (e.g., LangChain, LlamaIndex). Your expertise will cover the core components of the Gen AI stack:

- Retrieval: Implementing efficient and relevant information retrieval.
- Augmentation & Generation (RAG): Building robust RAG pipelines.
- Fine-Tuning: Fine-tuning embedding and generative models for specific tasks.
- Evaluation:



Establishing metrics and frameworks to evaluate model performance.

- LLMOps & Production Deployment: Manage the deployment of AI models as scalable inference endpoints. Implement and maintain LLMOps best practices, including CI/CD for models, observability, tracing, and version control using Git.
- Stakeholder Management & Enablement: Forge and manage strong relationships with customer leadership. Serve as the primary technical voice, educating stakeholders on the capabilities and limitations of AI, and conducting workshops to transfer knowledge and ensure successful adoption.

Skills and Qualifications:

- 5+ years of customer-facing experience in the design and implementation of AI/ML solutions.
- Proficient in Python and SQL.
- Expertise in AI frameworks and libraries, such as scikit-learn, Hugging Face Transformers, LangChain/Graph, GCP, and OpenAI APIs.
- Experience leading strategic, customer-facing initiatives and collaborating with business stakeholders to ensure ML solutions drive successful business outcomes, with a strong focus on teaching and enablement.
- Outstanding presentation skills to technical and executive audiences, whether impromptu on a whiteboard or using presentations and demos.
- Ability to work in a fast-paced environment and balance priorities across multiple projects at once.
- B.S. degree in a quantitative field such as Computer Science, Engineering, Mathematics, Statistics, or comparable degree/experience.
- Excellent communication skills in English

Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.

📌 AI/ML Engineer (Bengaluru)
🏢 66degrees
📍 Bengaluru