We are seeking a highly experienced AI & Generative AI Solution Architect to design and deliver impactful, scalable AI solutions for enterprise customers. This role combines deep technical expertise with strong client-facing capabilities, including working closely with CXOs, leading solution design, and driving pre-sales and implementation efforts.
You will act as a hands-on subject matter expert, translating complex business challenges into secure, scalable, and production-ready AI/ML and Generative AI architectures.
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
AI Architecture · Generative AI · Machine Learning · Data Science · RFP Solutioning · POCs · Cloud AI · NLP · Computer Vision · ML Deployment · Docker · Kubernetes
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