About this role
Relanto seeks an AI/ML Architect in Bengaluru, KA, IN, to lead the design, development, deployment and operation of cloud-based AI/ML and Generative AI solutions. The full-time role combines client-facing solution architecture, hands-on technical leadership and end-to-end delivery across domains including BFSI, retail, healthcare and manufacturing.
Responsibilities
- Gather business and technical requirements from clients and stakeholders; design scalable, cost-optimized AI/ML systems on AWS, GCP or Azure. Produce architecture diagrams, system designs and technical roadmaps, including data storage and retrieval strategies.
- Lead Generative AI and RAG solutions for enterprise knowledge management, chatbots and document summarization. Design LLM orchestration, prompts, retrieval optimization and grounding to improve output relevance and accuracy.
- Guide Python API development, data preprocessing and model training. Design ML deployment and CI/CD pipelines; establish monitoring, retraining, versioning, reproducibility, model lineage and auditability practices.
- Review designs, proofs of concept and code; mentor data scientists, ML engineers and developers. Coordinate with product, business analysis, data engineering and DevOps teams while managing technical delivery, timelines, resources and stakeholder expectations. Promote security, compliance, scalability and performance.
Required qualifications
- At least 7 years of overall IT experience designing, developing, deploying and operating AI/ML solutions, including a minimum of 3 years architecting end-to-end AI/ML solutions through production deployment.
- Experience with GenAI, LLMs, RAG, prompt engineering, LangChain or LlamaIndex, vector databases and unstructured-data retrieval. Knowledge of ML and deep learning algorithms, including CNNs, RNNs, LSTMs and Transformers, plus NLP applications such as language modeling, summarization, classification and named entity recognition.
- Strong Python expertise with PyTorch, TensorFlow, Hugging Face, NumPy and Pandas; cloud-native architecture on AWS, GCP or Azure; and model deployment through SageMaker, Vertex AI, Azure ML, containers or Kubernetes. Understanding of MLOps/LLMOps automation, model registries, monitoring and CI/CD, alongside communication, leadership and stakeholder management skills.
Preferred qualifications
AWS, GCP or ML-specialization certification, and experience leading large-scale AI transformation programs.
Skills for this role
AI/ML architectureGenerative AILarge Language ModelsRetrieval-Augmented GenerationPrompt engineeringLangChainLlamaIndexPineconeFAISSWeaviateElasticsearchMachine learningDeep learningNatural language processingCNNsRNNsLSTMsTransformersNamed entity recognitionPythonPyTorchTensorFlowHugging FaceNumPyPandasAWSGoogle Cloud PlatformAzureSageMakerVertex AI for ML deployment and CI/CD pipelinesor Azure ML. Define production