Artificial Intelligence Architect

6 days ago

Ahmedabad, Gujarat, India Armakuni Full time US$ 1,04,000 - US$ 1,30,878 per year

AI Architect Armakuni India

Role Summary:

Armakuni India is seeking a visionary AI Architect with deep technical expertise in AI/ML systems, Generative AI, and cloud-native architecture. This role demands hands-on leadership to define, design, and scale next-generation AI solutionsincluding LLMs, computer vision systems, and enterprise-grade ML platforms. You will drive innovation across the AI stack, shaping the future of data-driven product development at Armakuni.

Key Responsibilities:

  • Architectural Leadership

* Define and drive AI/ML architectural vision aligned with business objectives.

* Lead the design of scalable, secure, and cost-optimized AI platforms on AWS or similar clouds.

* Evaluate and select appropriate models, tools, and infrastructure for enterprise deployment.

  • Team & Technical Mentorship

* Guide and mentor engineers, data scientists, and MLOps professionals.

* Conduct architecture reviews, enforce coding and deployment standards.

* Foster a culture of experimentation, ownership, and knowledge sharing.

  • Generative AI & LLMs

* Architect and deliver GenAI solutions leveraging LLMs like GPT-4, Claude, Gemini, LLaMA, etc.

* Implement agentic workflows, RAG pipelines, and domain-specific LLM fine-tuning.

* Use advanced frameworks like LangChain, LangGraph, LangFuse, Crew AI, LLamaIndex.

  • Machine Learning Engineering

* Build robust ML pipelines: preprocessing, model training, evaluation, and drift monitoring.

* Apply classical ML, deep learning, and time series forecasting to solve real-world problems.

* Deploy and manage models using SageMaker and other MLOps tools.

  • Computer Vision (CV)

* Architect CV pipelines for image classification, object detection, segmentation, and more.

* Optimize models for cloud and edge deployment using PyTorch/TensorFlow.

  • Cloud & Infrastructure

* Lead cloud-native deployments using AWS (SageMaker, Bedrock, Lambda, etc.).

* Use containerization tools (Docker, Kubernetes) for scalable infrastructure.

* Integrate with RESTful APIs, vector databases (Pinecone, FAISS), and caching layers.

  • Core Skills & Technologies

* Languages & Libraries: Python, Scikit-learn, XGBoost, PyTorch, TensorFlow

* Generative AI Tools: LangChain, LangGraph, LLamaIndex, LangFuse, Crew AI

* Databases: PostgreSQL, DynamoDB, Redis, Chroma

* MLOps & Deployment: SageMaker, MLflow, FastAPI, Docker, Uvicorn

* Vector Search: Pinecone, FAISS, OpenSearch

* Cloud Platforms: AWS (preferred), GCP, Azure

  • Preferred Qualifications

* 8+ years in AI/ML, with 4+ years in GenAI and LLMs

* Proven track record in leading enterprise-grade AI deployments

* Open-source contributions or publications in AI/ML

* AWS AI/ML certification or equivalent is a strong plus

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