This role involves working in teams that use up-to-date agile technical practices - including continuous integration and deployment and fast feedback loops - to deliver timely and pragmatic solutions, as well as helping others to do their jobs in a more effective way.

Responsibilities
As a Gen AI Engineer, you will be responsible for designing, testing, and deploying GenAI solutions that leverage LLMs and related technologies. You ll work on solutions that incorporate prompt engineering, model evaluation, retrieval-augmented generation (RAG), and continuous performance monitoring, all while adhering to best practices in software engineering. This role blends data science, data engineering, and MLOps expertise, with a focus on making AI solutions reliable and production-ready.

Required Skills

- Solution Prototyping & Testing: Rapidly test various models and approaches to determine the best fit for the project without extensive over-investment. Stay updated on LLM advancements (e.g., GPT-3.5 to GPT-4).
- Prompt Engineering: Write, test, and refine prompts, including creating effective prompt chains and managing prompt versions for optimal results.
- Model & Prompt Evaluation: Analyze model and prompt performance to ensure reliability. Develop robust testing methodologies,



incorporating training and test sets for thorough evaluation.
- Performance Monitoring: Build pipelines to monitor model responses and track performance metrics in production for ongoing optimization.
- RAG Architecture Implementation: Design and maintain retrieval-augmented generation (RAG) architectures. Work with data pipelines, vector databases, and search algorithms. Manage document chunking and embedding selection for optimal context window usage.
- Data Extraction: Extract data from various sources (e.g., PDF as part of the RAG process.
- Software Development Best Practices: Employ CI/CD, test-driven development, and sound architectural principles in all GenAI solutions.
- Evaluation Scripts & Load Testing: Develop tests for the random nature of LLM outputs and conduct load testing to ensure system robustness, even when reliant on third-party APIs.
- ETL & Traditional Data Management: Build data pipelines to manage and integrate traditional relational data where necessary.

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.

📌 Lead Gen-AI Engineer (Bengaluru)
🏢 Equal Experts
📍 Bengaluru