AI Software Architect

Job Description

This role is for one of the Weekday's clients

Min Experience: 4 years

Location: Remote (India)

JobType: full-time

This role requires strong collaboration with engineering, product, and business teams to design robust AI architectures that align with organizational goals while ensuring scalability, performance, and responsible AI practices.

Requirements

Required Qualifications

• Over 4 years of experience in software engineering or architecture roles, with substantial exposure to AI/ML systems.
• Deep familiarity with modern neural network architectures including Transformers, CNNs, and RNNs.
• Proven experience in designing scalable and distributed architectures for AI-driven applications.
• Practical experience with cloud platforms like AWS, Azure, or Google Cloud.
• Skilled in containerization and orchestration technologies, particularly with Docker and Kubernetes.
• Strong comprehension of microservices architecture, RESTful APIs, and distributed system design.
• Experience with MLOps / LLMOps pipelines, including model training, deployment, monitoring, and lifecycle management.
• Adequate knowledge of large-scale data systems and contemporary database technologies.
• Capable of translating business requirements into scalable AI solution architectures.
• Exemplary documentation abilities for architectural designs, workflows, and technical decision-making processes.
• Comfortable in a startup or fast-paced environment with a strong sense of ownership and leadership.

Key Responsibilities

Design and manage the development of scalable generative AI systems and enterprise-grade AI platforms. Create robust architectures that facilitate model training, inference, monitoring, and lifecycle management within production settings. Lead the choice, customization, and enhancement of cutting-edge generative AI and large language models.

Develop and implement APIs, microservices, and integration frameworks to integrate AI functionalities into enterprise applications. Ensure that AI platforms adhere to high benchmarks for performance, reliability, security, and scalability, while also complying with data governance and privacy standards.

Work collaboratively with product, engineering, and business teams to define technical requirements and AI architecture approaches. Design end-to-end pipelines for the deployment and monitoring of AI models, ensuring smooth integration with existing systems.

Lead architectural choices for LLM applications, AI workflows, and distributed AI infrastructure. Establish best practices for responsible AI development, including protocols to address risks such as model hallucinations, bias, and reliability issues.

Offer technical guidance and mentorship to engineering teams while assisting in shaping long-term technology strategy and the evolution of AI platforms.

Preferred Qualifications

• Experience with Generative AI frameworks and orchestration tools such as LangChain, LangGraph, or comparable platforms.
• Knowledge of prompt engineering, LLM fine-tuning techniques (LoRA, RLHF, PEFT), and model optimization methods.
• Familiarity with performance optimization for AI workloads, including GPU/TPU acceleration, quantization, pruning, and model distillation.
• Experience with AI observability and monitoring tools for assessing model performance, drift, and anomalies.
• Understanding of AI governance, security, and compliance frameworks like GDPR or SOC 2.

Prior experience in building enterprise-scale AI or LLM-based products.

Skills

MLOps / LLMOps pipelines

AWS, Azure, or Google Cloud

RESTful APIs

Docker and Kubernetes