Gen AI Architect

Job Role Overview:

We are seeking an experienced Generative AI Solution Architect to join our team. This role requires a deep understanding of AI/ML models, especially generative AI technologies like GPT, DALL•E, Stable Diffusion, etc. The ideal candidate will be responsible for designing, developing, and deploying AI-driven solutions that leverage generative models to solve complex business challenges. You will work closely with cross-functional teams to align AI strategies with business objectives and drive innovation.

Key Responsibilities:

Strategic AI Solution Design:

Technology Selection & Evaluation:

Technical Leadership & Guidance:

Data Architecture & Management:

Scalability, Performance & Security:

Ethical AI & Compliance:

Stakeholder Communication:

Required Qualifications:

A bachelor's or master's degree or equivalent in computer science, Artificial Intelligence, or related field.

10-12 years of experience in AI development and architecture, with a focus on generative AI solutions specifically focused on designing and implementing AI/ML solutions in an enterprise environment.

Proven expertise in designing and deploying end-to-end machine learning pipelines. Strong understanding of various AI/ML techniques and algorithms (e.g., supervised, unsupervised, reinforcement learning, deep learning, NLP, computer vision).

Hands-on experience with at least one major cloud platform's AI/ML services (AWS, Azure, GCP).

Proficiency in programming languages commonly used in AI/ML (e.g., Python, R, Java). Familiarity with MLOps principles and tools for continuous integration, deployment, and monitoring of ML models.

Solid understanding of data governance, data quality, and data security principles. Excellent problem-solving, analytical, and critical thinking skills. Strong communication, presentation, and interpersonal skills, with the ability to influence and collaborate effectively across diverse teams

Required Skills:

Experience with Generative AI models (LLMs, diffusion models) and related frameworks (e.g., LangChain, LlamaIndex). Experience with big data technologies (e.g., Spark, Hadoop, Kafka).

Certifications in relevant cloud AI/ML platforms (e.g., AWS Certified Machine Learning Specialty, Google Cloud Professional Machine Learning Engineer). Experience with agile development methodologies