Key job responsibilities
* Architecture & Design: Design and architect end-to-end AI-powered application solutions aligned with customer business objectives and technical requirements.
* Define application architecture patterns, standards, and best practices for AI/ML integration on our company.
* Create technical roadmaps for customer AI application development and modernization initiatives.
* Evaluate and recommend our AI/ML services and technologies including Amazon Bedrock, SageMaker, and generative AI solutions.
* Design data pipelines and ETL processes to support AI model training and inference using our services.
* Customer Engagement & Consulting:
Lead customer engagements from discovery through implementation, serving as trusted technical advisor.
* Conduct AI readiness assessments and develop adoption strategies tailored to customer maturity levels.
* Facilitate architecture workshops and design sessions with customer stakeholders.
* Deliver Well-Architected reviews focused on AI/ML workloads.
* Build strong relationships with customer technical teams and executive leadership.
* Guide customers in constructing AI processes aligned with AWS best practices.
* Technical Leadership: Lead cross-functional teams in implementing AI solutions from concept to production.
* Provide technical guidance on AI model integration, deployment strategies, and optimization on our company.
* Conduct architecture reviews ensuring solutions meet scalability, performance, security, and cost-efficiency requirements.
* Mentor customer teams and junior ProServe consultants on AI best practices and AWS technologies.
* Collaborate with data scientists, ML engineers, and software developers to translate AI models into production applications.
* AI Solution Development: Design architectures for generative AI applications including RAG (Retrieval-Augmented Generation) systems, chatbots, and intelligent agents using our Bedrock.
* Architect real-time and batch AI inference pipelines with appropriate monitoring and observability.
* Implement MLOps practices using SageMaker for model versioning, deployment automation, and continuous improvement.
* Design solutions for responsible AI including bias detection, explainability, and governance frameworks.
* Optimize AI application performance, cost, and resource utilization across AWS services.
Knowledge Sharing & Thought Leadership:
* Develop reusable assets, reference architectures, and best practice documentation.
* Contribute to AWS ProServe knowledge base and customer-facing content.
* Present at customer events, workshops, and industry conferences.
* Stay current with emerging AI technologies and AWS service innovations.
* Share learnings across the ProServe organization.
Basic Qualifications
– 10+ years of experience in application architecture and software development.
– 5+ years of hands-on experience with AI/ML technologies and frameworks (TensorFlow, PyTorch, scikit-learn, Hugging Face).
– Deep expertise in AWS cloud platform with focus on AI/ML services (SageMaker, Bedrock, Comprehend, Rekognition, etc.).
– Proficiency in programming languages such as Python, Java, or similar.
– Strong knowledge of generative AI technologies including LLMs, prompt engineering, fine-tuning, and RAG architectures.
– Understanding of various AI domains: NLP, computer vision, recommendation systems, predictive analytics.
– Willingness to travel to customer sites as needed.
