Lead AI Engineer

Job Description: We are seeking a Lead Generative AI Engineer with strong foundations in deep learning, transformer architecture, and practical experience building Gen AI applications beyond basic RAG systems. The ideal candidate has hands-on experience/technical familiarity with LLM fine-tuning, multimodal models, retrieval systems, agentic frameworks, retrieval architectures, and production-grade ML deployment. This role will partner with engineering, data science, and CX teams to build intelligent agents, multimodal experiences, personalization systems, and knowledge-grounded AI solutions that power the future of customer engagement for global brands. Key

RESPONSIBILITIES

Generative AI, Multimodal Systems & Agentic Frameworks Build conversational and non-conversational, multimodal, and agentic AI applications using LLMs and frameworks such as Lang Chain, Lang Graph, Llama Index, Auto Gen, or similar. Design AI workflows incorporating reasoning, planning, tool-use, memory, grounding, and external system integrations. Develop Knowledge Graph (KG)-assisted AI systems, including entity extraction, linking, and KG-augmented retrieval. Ensure safety, consistency, and hallucination-control through structured evaluation and guardrails. Deployment, APIs & Cloud Engineering Transform models into scalable APIs and microservices using Python, Fast API/Flask, Docker. Deploy and monitor ML/AI systems in AWS/Azure/GCP, optimizing for cost, latency, and reliability. Collaborate with MLOps teams on CI/CD pipelines, model versioning, monitoring, and automated evaluation. Work with big data technologies including Apache Spark, Hadoop, and No SQL databases such as Mongo DB. Model Development & Applied AI Engineering Build and optimize transformer-based and multimodal models using deep learning frameworks (e.g., Py Torch, Tensor Flow). Implement fine-tuning, alignment (RLHF/RLAIF), Lo RA/QLo RA, pruning, and model evaluation pipelines. Develop information retrieval systems, including hybrid dense–sparse retrieval, ranking, knowledge graphs, and relevance optimization. Build predictive models and ML pipelines from scratch, including data preparation, feature engineering, and model selection. Collaboration, Documentation & Mentorship Work cross-functionally with CX, engineering, and product stakeholders to translate business needs into AI solutions. Document models, experiments, evaluation frameworks, and deployment processes. Mentor junior engineers and contribute to internal best practices, reusable components, and R&D initiatives. Must Have : Minimum 5+ years of hands-on software development experience including building and deploying machine learning models into production. 2+ years of experience working with deep learning, Gen AI, or transformer-based architectures. Demonstrated experience building Gen AI applications beyond simple RAG (e.g., agents, multimodal, custom LLM fine-tuning). Experience integrating AI systems in enterprise-grade environments. Technical Skills : Programming: Python (advanced), SQL; robust experience with API development and data engineering, Backend Frameworks: Flask, FASTAPI, Django Machine Learning: Predictive modelling, deep learning, optimization, embeddings, vector search, model evaluation. Generative AI: LLMs, RAG, multimodal architectures, agents, prompt engineering, grounding, knowledge graphs. Cloud Platforms: AWS, Azure, or GCP with hands-on experience deploying and scaling AI systems. Data Technologies: Apache Spark, Hadoop, Mongo DB; strong understanding of data pipelines and large-scale processing. Math Foundations: Linear algebra, probability, statistics. Location: DGS India

• Bengaluru
• Bhartiya City Block 1 (inactive) Brand: Merkle Time Type: Full time Contract Type: Permanent Can’t find a suitable job?

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