We are looking for a
Solution Architect to join our client, an
innovator in the Lifesciences AI space. This is a
hybrid role in
Tarrytown, NY or Basking Ridge, NJ with 3 days onsite/week.
Overview 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 - Solution Design & Architecture:
- 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
- Deployment Platforms: Cloud platforms (e.g., AWS, Azure )
- Architect solutions for real-time generative AI use cases (e.g., chatbots, content creation, synthetic data generation) and batch processing.
- Intelligent Document 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 implement automation 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.
- Collaboration & Innovation:
- 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.