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Open nowPosted 157 days ago

AI/ML Architect

Relanto40 open roles

Where
Bengaluru
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Your applicationOpen nowAI/ML ArchitectRelanto · Bengaluru

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  6. 44.6%60 days
This job: posted 157 days ago

The posting

Job Summary

We are seeking an experienced and visionary AI/ML Architect to lead the end-to-end design, development, deployment, and operationalization of advanced AI/ML and Generative AI (GenAI) solutions on cloud platforms. The ideal candidate will possess deep technical expertise in ML architecture, GenAI frameworks, Retrieval-Augmented Generation (RAG) pipelines, cloud-native deployment, and MLOps practices. You will work closely with cross-functional teams, clients, and engineering teams to define scalable AI strategies and deliver cutting-edge solutions across various domains.

Key Responsibilities

Customer Engagement & Solution Architecture

  • Interact with clients and stakeholders to gather business and technical requirements and translate them into scalable AI/ML solutions.
  • Architect and design AI/ML systems across AWS, GCP, or Azure with a strong focus on cloud-native and cost-optimized architecture.
  • Create detailed system design documents, architecture diagrams, and technical roadmaps.
  • Define data architecture, storage, and retrieval strategies tailored to AI/ML workflows.

GenAI & RAG Architecture

  • Lead the design and implementation of Generative AI solutions using LLMs, LangChain, LlamaIndex, Prompt Engineering, and vector databases such as Pinecone, FAISS, Weaviate, or Elasticsearch.
  • Architect RAG (Retrieval-Augmented Generation) pipelines for enterprise use cases including knowledge management, chatbot development, and document summarization.
  • Implement prompt orchestration, retrieval optimization, and grounding techniques to enhance LLM output accuracy and relevance.

AI/ML Model Development & MLOps

  • Guide the development of Python-based APIs, data preprocessing workflows, and model training pipelines.
  • Design and implement robust CI/CD pipelines for ML model deployment using tools like SageMaker, Vertex AI, or Azure ML.
  • Define and implement model monitoring, retraining, and performance management strategies for production-grade ML systems.
  • Ensure best practices in versioning, reproducibility, model lineage, and auditability (MLOps/LLMOps).

Technical Leadership & Governance

  • Review and approve system designs, PoCs, and implementation approaches.
  • Provide hands-on leadership and mentorship to data scientists, ML engineers, and software developers.
  • Lead architectural decision-making, code quality reviews, and sprint grooming sessions.
  • Champion best practices in security, compliance, scalability, and performance optimization for AI/ML solutions.

Project Management & Collaboration

  • Own end-to-end technical delivery of AI/ML and GenAI projects across multiple domains (e.g., BFSI, Retail, Healthcare, Manufacturing).
  • Coordinate with product owners, business analysts, data engineers, and DevOps teams to ensure seamless delivery.
  • Manage stakeholder expectations, project timelines, and resource allocation efficiently.

Required Qualifications

  • 7+ years of overall IT experience in designing, developing, deploying, and operationalizing AI/ML solutions.
  • Minimum 3 years of experience in architecting end-to-end AI/ML solutions, including design, implementation, and production deployment.
  • Proven experience in GenAI, LLMs, RAG architecture, prompt engineering, and orchestration tools like LangChain, LlamaIndex, etc.
  • Hands-on with vector databases (e.g., Pinecone, FAISS, Elasticsearch) and unstructured data retrieval.
  • Deep knowledge of Machine Learning and Deep Learning algorithms: CNNs, RNNs, LSTMs, Transformers, etc.
  • Experience in Natural Language Processing (NLP), including language modeling, summarization, classification, and NER.
  • Strong expertise in Python, with frameworks like PyTorch, TensorFlow, HuggingFace, NumPy, and Pandas.
  • Demonstrated experience in designing cloud-native AI/ML solutions on AWS, GCP, or Azure.
  • Skilled in deploying models via services like SageMaker, Vertex AI, Azure ML, or using containers and Kubernetes.
  • Solid understanding of MLOps/LLMOps lifecycle: pipeline automation, model registry, monitoring, CI/CD.
  • Excellent communication, leadership, and stakeholder management skills.

Preferred Qualifications

  • Certification in AWS/GCP or ML specializations.
  • Experience in leading large-scale AI transformation programs.

Why Join Us?

  • Work with cutting-edge GenAI and AI/ML technologies and projects.
  • Collaborate with top-tier clients and drive real-world impact.
  • Leadership opportunities in a growing AI/ML practice.
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