AIML Architect

Role: AIML Architect.
Job Overview:
We are seeking a skilled AI/ML Architect with strong expertise in AWS and Generative AI
(GenAI), along with a solid foundation in Data Engineering and Machine Learning. The ideal
candidate will play a key role in shaping end-to-end AI/ML and GenAI solutions—from data
architecture to model deployment—ensuring designs are scalable, secure, cost-efficient,
and aligned with business outcomes.
Key Responsibilities:
• Define and lead end-to-end AI/ML and Generative AI solution architectures,
covering data, model, application, and integration layers.
• Create architecture diagrams and design frameworks addressing scalability, cost
optimization, performance, security, and enterprise adoption.
• Collaborate with business and technical stakeholders to identify use cases and
translate them into production-ready AI/ML and GenAI solutions.
• Influence and align client VPs, Directors, and senior stakeholders on architecture
decisions, roadmaps, and solution approaches.
• Architect and implement data pipelines and feature engineering frameworks for
structured and unstructured data.
• Design and oversee the full ML lifecycle, including data preparation, model
development, evaluation, deployment, and monitoring.
• Drive adoption of MLOps and LLMOps practices, including CI/CD pipelines, model
governance, prompt/version management, and retraining strategies.
• Leverage AWS cloud services (SageMaker, Bedrock, Lambda, S3, EMR, etc.) to
build scalable AI platforms.
• Apply Design Thinking principles to ensure user-centric and business-aligned
solutions.
• Mentor engineering and data science teams on architecture patterns, performance
optimization, and system integration.
Required Qualifications:
• Bachelor's or master’s degree in computer science, Data Science, Engineering, or a
related field.

• 12+ years of experience in software/data engineering, with at least 4+ years in AI/ML
solution architecture.

• Strong expertise in data engineering (ETL pipelines, data lakes/warehouses, real-
time data processing).

• Hands-on experience with ML frameworks (TensorFlow, PyTorch, Scikit-learn) and
platforms (SageMaker, Azure ML, GCP AI).
• Deep understanding of MLOps principles and tools (MLflow, Kubeflow, Airflow,
Docker, Kubernetes).
• Strong knowledge of AWS and Azure or GCP is good to have.
• Strong problem-solving and communication skills, with a passion for
applying Design Thinking to deliver impactful solutions.
• Familiarity with data privacy, compliance, and ethical AI considerations.
Preferred Qualifications:
• Certifications in AI/ML or Cloud Architecture (e.g., AWS Certified Machine Learning –
Specialty).
• Experience in product/platform-based AI solutions.
• Exposure to NLP, computer vision, or generative AI is a plus.