Overview
The primary responsibility of this role is to act as an AWS Agentic Product Engineer in
medium-to-large opportunities for mid-sized clients; that may involve solutioning including
but not limited to understanding client requirements, designing reusable AI assets,
developing agentic workflows, engineering cloud-native AI products, and establishing
scalable deployment frameworks. Mid-market organizations increasingly require AI
enabled products that can be deployed rapidly, reused across multiple engagements, and
adapted to changing business requirements.
The role requires the ability to combine software engineering, cloud infrastructure,
automation, testing, and AI innovation to create differentiated solutions.
Key Responsibilities
Solution Engineering, Product Strategy & Asset Development
Translate business and technical requirements into reusable AI-enabled product assets
using AWS-native services and modern engineering practices.
Collaborate with Sales Pursuit, Solution Architects, Engineering, and Delivery Teams to
develop scalable and repeatable AI offerings.
Design and build reusable agentic AI-enabled solutions that accelerate deployment and
adoption across multiple client engagements. Drive innovation through proof-of-concepts, pilot solutions, and packaged AI assets.
AWS Agentic Product Architecture
Design reusable agent configurations, orchestration frameworks, and AI workflow
architectures.
Build scalable infrastructure-as-code templates and deployment accelerators using AWS
services. Define reference architectures supporting agentic AI, intelligent automation, and AI
native applications. Integrate AI products with enterprise systems, APIs, data platforms, and cloud services.
Optimize architecture patterns for reusability, maintainability, and deployment
efficiency. Engineering Excellence, Testing & Quality Assurance
Develop robust evaluation, testing, validation, and monitoring frameworks for AI
enabled products. Implement automated testing approaches that ensure quality, reliability, and
performance consistency. Establish engineering standards, coding practices, and governance frameworks for
reusable assets. Support product lifecycle management, version control, release management, and
continuous improvement. Identify opportunities to improve engineering productivity through automation and
reusable accelerators. Client Engagement & Collaboration
Partner with architects, delivery teams, product owners, and business stakeholders to
align solutions with business objectives.
Participate in discovery sessions, architecture reviews, and product roadmap
discussions. Provide technical advisory support for reusable AI products and cloud-native solution
architectures. Communicate engg decisions, product capabilities, and solution benefits to
stakeholders.
Thought Leadership & Innovation
Contribute to AI product innovation strategies and reusable asset development
initiatives. Mentor engineering teams on AI product development, cloud engineering, and agentic
architecture principles. Contribute to reusable frameworks, accelerators, best practices, and thought leadership
activities.
Experience
Minimum 5–8 yrs exp in Product Engineering, S/W Engineering, Cloud
Enggg, AI Engg, or related domains.
Experience designing and building cloud-native apps and reusable software
assets on AWS. Experience developing AI, machine learning, automation, or intelligent workflow
solutions, infrastructure-as-code, CI/CD pipelines, and automated
deployment frameworks. Demonstrated ability to translate business requirements into scalable product
architectures. Experience developing proof-of-concepts, reusable accelerators, testing frameworks,
and productized assets. Experience supporting enterprise AI transformation and cloud modernization
initiatives.