GenAI Engineer.
This mandate is run by SYMPHONI HR, a Mumbai-based executive search firm, est. 2003. Applications are email-verified and reach the search team running the role — confidentially, always.
About the organisation.
Our client is a prominent global player in the computer software industry, known for delivering innovative digital solutions to enterprise clients. They foster a collaborative, high-performance culture that prioritizes technological advancement and continuous learning. With a focus on scaling cutting-edge AI capabilities, they provide an environment where technical experts can drive significant business impact.
About the role.
We are seeking a highly skilled GenAI Engineer to join a dynamic technical team focused on designing, developing, and deploying advanced Generative AI solutions. In this role, you will leverage Large Language Models to solve complex business challenges and drive innovation across the organization. You will work in a hybrid capacity to build scalable, production-grade AI systems that integrate seamlessly into existing software ecosystems.
What you will do.
- Architect and implement scalable production LLM pipelines to support enterprise-grade applications.
- Design and optimize RAG (Retrieval-Augmented Generation) architectures to enhance model accuracy and context relevance.
- Develop sophisticated prompt engineering strategies to improve output quality across various use cases.
- Build automated document processing and extraction workflows to streamline data ingestion and analysis.
- Collaborate with cross-functional teams to integrate AI capabilities into existing software ecosystems.
- Manage the full lifecycle of AI model deployment in production environments.
What you bring.
- Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, or a related technical field.
- Proven expertise in Generative AI and LLMs with a focus on real-world application.
- Strong proficiency in LangChain for building complex AI-driven workflows.
- Hands-on experience with AWS cloud infrastructure for hosting and scaling AI models.
- Demonstrated ability to manage the full lifecycle of AI model deployment in production environments.
- Experience with vector databases such as Pinecone, Milvus, or Weaviate is highly desirable.
- Familiarity with fine-tuning open-source models like Llama or Mistral.
- Solid background in Python development and MLOps best practices.
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