Solution Architect - Generative AI

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Seeking a Solution Architect to design, develop, and implement cutting-edge solutions leveraging generative AI technology , integration and Digital automation . The ideal candidate will play a pivotal role in architecting scalable, secure, and efficient applications that transform business processes, enhance decision-making, and deliver measurable value. This role requires a good understanding of architecture, AI/ML frameworks, Cloud, and modern automation tools, combined with a passion for solving complex problems.

Key Responsibilities

• Design end-to-end technical architectures for applications utilizing generative AI (e.g., LLMs, GANs), intelligent document processing (e.g., OCR, NLP, data extraction), and workflow automation.
• Define system components, integrations, APIs, and data flows to ensure scalability, performance, and reliability.
• Collaborate with product managers, developers, and stakeholders to translate business requirements into technical architecture.
• Document and present architecture, along with pros & cons to senior IT leadership
• Components of architecture:
• Generative AI:
• Create application architecture to integrate generative AI models (e.g., GPT-based models, diffusion models) into applications., including:
• Foundation Models: Leverage large language models (LLMs) like GPT-4o, LLaMA, Grok, or BERT, and generative adversarial networks (GANs) such as Stable Diffusion or VAE-based systems for text, image, audio, or multimodal generation.
• Frameworks & Libraries: Utilize Hugging Face Transformers, LangChain, and DeepSpeed
• Orchestration & Pipelines: Tools like Apache Airflow, Kubeflow, or MLFlow
• Architect solutions for real-time generative AI use cases (e.g., chatbots, content creation, synthetic data generation) and batch processing.
• Architect solutions for automated document ingestion, classification, data extraction, and validation using IDP technologies (e.g., OCR, NLP, computer vision).
• Ensure seamless integration of IDP systems with existing enterprise platforms (e.g., ERP, CRM).
• Enhance document processing workflows with AI-driven insights and error reduction.
• Automation:
• Develop and implementautomation strategies using tools like RPA (Robotic Process Automation), low-code platforms, or custom scripts to streamline repetitive tasks.
• Integrate automation workflows with AI-driven decision-making systems.
• Monitor and optimize automated processes for efficiency and adaptability.
• Integration:
• Define system components, integrations, APIs, and data flows to ensure scalability, performance, interoperability, and reliability.
• Design and implement the integration technology stack to connect generative AI, IDP, and automation systems with enterprise ecosystems, including:
• Middleware & ESB:Utilize tools like Apache Camel, MuleSoft, or Red Hat Fuse for enterprise service bus (ESB) integration
• API Management:Leverage platforms like Apigee, Kong, or AWS API Gateway for secure and scalable API design and orchestration.
• Messaging Systems:Implement real-time data exchange with Apache Kafka, RabbitMQ, or Azure Service Bus.
• Identity & Access Management:Integrate with OAuth 2.0, OpenID Connect, or SAML via tools like Okta or Keycloak for secure system access.
• Ensure seamless interoperability between cloud, on-premises, and third-party systems.
• Technical Leadership:
• Provide technical guidance to development teams during implementation, ensuring adherence to architectural standards.
• Conduct code reviews, performance tuning, and troubleshooting of complex issues.
• Work closely with cross-functional teams (e.g., data science, DevOps, security) to ensure seamless deployment and operation of solutions.
• Identify opportunities to leverage emerging technologies to improve existing systems.
• Contribute to proofs-of-concept (PoCs) and pilot projects to validate new ideas.
• Compliance & Security:
• Ensure solutions comply with industry standards, data privacy regulations (e.g., GDPR, CCPA), and security best practices.
• Design systems with robust authentication, encryption, and auditability features.

Qualifications

• Experience:
• 10+ years of experience in solution architecture, software engineering, or a related role.
• Proven expertise in designing and deploying applications with generative AI technologies (e.g., TensorFlow, PyTorch, Hugging Face Transformers).
• Hands-on experience with intelligent document processing tools (e.g., ABBYY, UiPath Document Understanding).
• Strong background in automation technologies (e.g., UiPath, Python scripting).
• Experience with cloud platforms (e.g., AWS, Azure, Google Cloud) and microservices architecture.
• Technical Skills:
• Proficiency in programming languages such as Python, Java, or C#.
• Familiarity with AI/ML frameworks, APIs, and model deployment (e.g., ONNX, Docker, Kubernetes).
• Knowledge of database systems (SQL, NoSQL) and data pipeline tools (e.g., Apache Kafka, Airflow).
• Understanding of DevOps practices, CI/CD pipelines, and infrastructure-as-code (e.g., Terraform).
• Soft Skills:
• Exceptional problem-solving and analytical skills.
• Strong communication skills to articulate complex technical concepts to non-technical stakeholders.
• Ability to work collaboratively in a fast-paced, agile environment.
• Preferred Qualifications:
• Certifications in cloud architecture (e.g., AWS Certified Solutions Architect, Azure Solutions Architect).
• Experience with enterprise-scale deployments in industries like finance, healthcare, lifescience.

Seniority level

• Seniority level

  Mid-Senior level

Employment type

• Employment type

  Full-time

Job function

• Job function

  Engineering and Information Technology

• Industries

  IT Services and IT Consulting

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