AI Engineer - RAG Pipelines

Role Overview:

We are seeking a seasoned AI Engineer to join our high-impact team in Bangalore, where you will be at the forefront of building next-generation intelligent systems. In this role, you will design, develop, and deploy sophisticated Generative AI solutions that transform complex data into actionable business intelligence. You will collaborate closely with cross-functional product teams, data scientists, and key stakeholders to bridge the gap between cutting-edge research and scalable production applications. By architecting robust RAG pipelines and LLM-driven workflows, you will directly influence our product roadmap, significantly enhancing user experience and driving measurable efficiency gains across our enterprise platforms.

Key Responsibilities:

• Architect and implement scalable RAG (Retrieval-Augmented Generation) pipelines to ensure high-accuracy, context-aware responses for end-users.

• Develop and optimize complex LLM workflows using LangChain and LangGraph to automate multi-step reasoning tasks and improve system reliability.

• Integrate Generative AI models into existing production environments to solve real-world business challenges and improve operational throughput.

• Collaborate with engineering teams to fine-tune model performance, ensuring low-latency and high-quality outputs that meet stringent production standards.

• Mentor junior engineers and contribute to technical design reviews to foster a culture of excellence and continuous innovation within the AI practice.

Required Skillset:

• Demonstrated expertise in building and deploying production-grade Generative AI applications, with a deep understanding of LLM orchestration frameworks like LangChain and LangGraph.

• Proven ability to design and maintain RAG architectures that handle large-scale, unstructured datasets effectively.

• Strong proficiency in Python and modern software engineering practices, with a focus on writing clean, maintainable, and efficient code.

• Exceptional communication skills, with the ability to translate complex technical concepts into clear strategies for non-technical stakeholders and leadership.

• A collaborative mindset, comfortable working in a hybrid office environment in Bangalore, and capable of driving projects independently in a fast-paced, high-growth setting.

• A solid academic foundation in Computer Science, Artificial Intelligence, or a related quantitative field, supported by 4 - 12 years of hands-on experience in the AI/ML domain.