AI Solutions Architect (Presales & Delivery)
Must Have Skills
Preferred Skills
About Us: We are calling candidates on behalf of a Software Solutions company headquartered in East Brunswick, NJ. Incorporated in 2003, it provides comprehensive range of solutions in the area of GRC, Technology, Procurement, Healthcare Provider and Oracle to customers across the globe. Combining our unparalleled experience of over a decade in the software industry and global reach, we have grown with extensive capabilities across industry verticals
Key Responsibilities
Customer Consulting & Presales
Engage with customers to understand business objectives, pain points, and transformation opportunities. Conduct discovery workshops and identify high-value AI use cases. Collaborate with Sales teams to develop AI-led solution strategies. Lead technical presentations, solution demonstrations, and executive discussions. Develop solution proposals, architecture documents, effort estimates, SOWs, and responses to RFPs/RFIs. Support customer decision-making and drive successful deal closures.
AI Solution Architecture
Design scalable, secure, and cloud-native AI solutions leveraging Generative AI, LLMs, RAG, AI Agents, Machine Learning, NLP, Intelligent Automation, and Predictive Analytics. Define end-to-end solution architecture, integration strategy, security, governance, and implementation roadmap. Ensure solutions align with enterprise architecture standards and business objectives. AI-Enabled Software Engineering
Drive AI adoption across enterprise application architecture and the Software Development Lifecycle. Design AI-enabled full-stack applications by integrating LLMs, copilots, semantic search, AI agents, and intelligent automation into web, mobile, API, and enterprise platforms. Architect modern cloud-native, microservices-based applications with scalable backend, frontend, API, and data architectures. Establish engineering best practices for AI integration, DevSecOps, CI/CD, observability, and Responsible AI. Proof of Concept & Delivery
Develop rapid AI Proof of Concepts (PoCs) and prototypes demonstrating business value and technical feasibility. Lead architectural governance from presales through implementation. Collaborate with engineering, cloud, security, and delivery teams to ensure successful execution. Mentor technical teams and promote reusable AI accelerators and best practices. Innovation
Stay current with emerging AI technologies and industry trends. Contribute to AI capability development, reusable frameworks, reference architectures, and thought leadership initiatives.
Required Qualifications Bachelor's or Master's degree in Computer Science, Engineering, Artificial Intelligence, or a related discipline. 10+ years of experience in enterprise software development, solution architecture, or technology consulting. 5+ years of hands-on experience designing and implementing AI/ML and Generative AI solutions. Proven experience in customer-facing presales, solution consulting, and enterprise architecture. Experience leading multidisciplinary teams in enterprise software delivery.
Technical Skills Artificial Intelligence Generative AI, Large Language Models (LLMs), RAG, AI Agents, Machine Learning, NLP, Computer Vision, Intelligent Automation, Prompt Engineering, MLOps, Responsible AI.
AI Platforms & Frameworks Azure OpenAI, Azure AI Foundry, OpenAI APIs, AWS Bedrock, Google Vertex AI, LangChain, LangGraph, LlamaIndex, Semantic Kernel, Hugging Face, Vector Databases.
Software Engineering Python, Java, .NET, Node.js, React/Angular, REST APIs, Microservices, Event-Driven Architecture, SQL/NoSQL Databases, API Integration.
Cloud & DevOps Microsoft Azure, AWS, GCP, Docker, Kubernetes, GitHub, Azure DevOps, CI/CD, Terraform, DevSecOps.
Core Competencies AI Solution Architecture Enterprise Application Architecture Technical Presales & Customer Consulting Full-Stack Software Engineering Proof of Concept Development
Cloud Architecture Executive Communication & Presentation Proposal Development & Solution Estimation
Stakeholder Management Technical Leadership & Mentoring Strategic Problem Solving Innovation & Continuous Learning
Success Measures Successful conversion of AI opportunities into customer engagements. High-quality AI solution architectures and technical proposals. Effective PoCs leading to production implementations. Successful AI adoption across enterprise software solutions. Customer satisfaction, delivery excellence, and architecture governance. Contribution to reusable AI assets, accelerators, and organizational capability development.
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