AI System Architect

3 weeks ago

Hyderabad, Telangana, India AICraft Full time
Job Description

Job Summary

The AI System Architect leads the design, development, and implementation of advanced AI/ML systems and infrastructure across the enterprise. This role transforms business needs into robust, scalable, and secure AI solutions, driving digital transformation and innovation. The AI System Architect collaborates closely with data scientists, ML engineers, DevOps, and business stakeholders to deliver production-grade AI systems that power critical organizational functions.

Key Responsibilities

- Design end-to-end AI architectures, including data pipelines, model development workflows, deployment strategies, and system integration.
- Develop, prototype, and operationalize scalable AI/ML models, with a focus on performance, security, and reliability.
- Select and implement appropriate AI tools, frameworks (e.g., TensorFlow, PyTorch), and platforms for diverse application needs.
- Collaborate with cross-functional teams to integrate AI into products, services, and cloud/edge environments.
- Oversee the lifecycle of AI projects: from requirements gathering, technical design, and development to production deployment and ongoing optimization.
- Lead intelligent agent/LLM system design, orchestration, and real-time analytics for contextual and autonomous workflows.
- Ensure compliance with regulatory, ethical, and security standards related to AI and data.
- Mentor and provide technical leadership for AI engineering teams; set best practices for code quality, MLOps, and CI/CD automation.
- Monitor technology trends; drive continuous improvement and innovation across AI system designs.

Required Qualifications

- Bachelors or Masters degree in Computer Science, Artificial Intelligence, Engineering, or a related technical field.
- 510 years of professional experience in AI architecture, AI/ML engineering, or intelligent systems design.
- Proven track record designing and implementing large-scale, production-grade AI solutions
- Advanced programming skills in Python (and optionally R, Java); hands-on experience with cloud platforms (AWS, Azure, GCP) and containerized AI delivery (Docker, Kubernetes).
- Extensive experience with AI/ML frameworks (TensorFlow, PyTorch, scikit-learn), agent orchestration, and workflow automation tools.
- Strong understanding of data engineering, MLOps practices, API design, and real-time analytics.
- Excellent problem-solving, communication, and leadership skills; ability to translate business goals into technical solutions.
- Proven ability to work collaboratively across multidisciplinary teams, with a preference for experience in fast-paced or large enterprise environments.

Preferred/Bonus Qualifications

- Experience with LLM platforms, agentic systems, and retrieval-augmented generation (RAG).
- Familiarity with model governance, XAI (Explainable AI), and regulatory frameworks (GDPR/SOC 2).
- Expertise in high-throughput, distributed, or cloud-native architecture.

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