AI and GenAI Solution Architect

This role is for one of the Weekday's clients

Salary range: Rs 1800000 - Rs 4000000 (ie INR 18-40 LPA)

Requirements

Key Responsibilities

• Lead the design and architecture of end-to-end AI, ML, and Generative AI solutions.
• Act as a trusted advisor to customers by understanding business challenges and translating them into AI-driven solutions.
• Own technical solutioning for RFPs, including architecture design, implementation approach, and delivery methodology.
• Design robust, scalable, and secure solution architectures, including high-level and low-level designs, data flows, and integration with existing systems.
• Develop solution proposals with clear narratives, architecture diagrams, and technical justification for design decisions.
• Select appropriate AI/ML and GenAI models based on problem type, data characteristics, and business requirements.
• Define strategies for data preprocessing, feature engineering, model training, evaluation, and deployment.
• Address model explainability, bias mitigation, governance, and ethical AI considerations.
• Collaborate with engineering teams to build proofs of concept (POCs) and pilot implementations.
• Leverage reusable AI accelerators and frameworks to speed up pre-sales demos and solution delivery.
• Stay current with emerging trends and advancements in Generative AI and applied ML.
  

Qualifications & Experience

• Bachelor's or Master's degree in Computer Science, Engineering, or a related field.
• 8+ years of experience designing and delivering AI/ML and Generative AI solutions.
• Proven ability to translate business requirements into scalable AI architectures.
• Strong foundation in machine learning principles, algorithms, and best practices.
• Hands-on experience with Python and ML frameworks such as Pandas, TensorFlow, and PyTorch.
• Expertise in deploying AI/ML solutions on cloud platforms (AWS, Azure, GCP).
• Deep knowledge of Generative AI platforms and models, including Azure OpenAI, Google AI, AWS Bedrock, Anthropic, NVIDIA NeMo, Microsoft Copilot, and open-source LLMs.
• Experience with NLP use cases such as text classification, sentiment analysis, and language translation.
• Working knowledge of computer vision and reinforcement learning concepts.
• Familiarity with GPU-based computing, CUDA, and NVIDIA AI frameworks.
• Experience with model deployment, containerization, and orchestration tools (Docker, Kubernetes).
  

Key Skills

• Generative AI
• Machine Learning
• Data Science
• RFP Solutioning
• POCs
• Cloud AI
• NLP
• Computer Vision
• ML Deployment
• Docker
• Kubernetes