Pasay City Jobs Solutions Architect – Sr Manager, Digital Transformation And Solutioning Position at EXL Service Philippines, Inc.

Job Info

Company	EXL Service Philippines, Inc.
Position	Solutions Architect - Sr Manager, Digital Transformation And Solutioning
Region	Pasay City
Career Level	Assistant Manager/Manager
Work Experience	5 years
Qualification	Bachelor's/College Degree
Type of Work	Full-Time
Minimum Salary	PHP 16.000
Maximum Salary	PHP 38.000

Job Summary

We are seeking a highly skilled and experienced Solutions Architect to join our dynamic Digital Transformation Team. As a Solutions Architect, you will play a pivotal role in driving our organization’s digital transformation initiatives, with a focus on leveraging cutting-edge technologies such as Machine Learning (ML), Natural Language Processing (NLP), Generative AI, Conversation AI, Intelligence Document Processing (IDP) and other artificial intelligence techniques. Your expertise in the healthcare domain and successful project deployments in relevant fields will be instrumental in delivering innovative and transformative solutions.

In this role, the successful candidate will collaborate closely with our talented team of Project Managers, Digital Transformation Leaders, Data Scientists, Software Engineers, and healthcare domain experts to translate business challenges into innovative AI-driven solutions. Possessing an end-to-end perspective, you will navigate projects from their conceptualization to full-scale deployment, while ensuring data privacy and regulatory compliance, which will be crucial in delivering successful outcomes that positively impact patient care and operational efficiency

Responsibilities:

1. Digital Transformation Strategy: Collaborate with key stakeholders and business leaders to understand business objectives and challenges. Develop digital transformation strategies that leverage Machine Learning, NLP, Generative AI, and other AI technologies to address specific healthcare industry needs.

1. Architecture Design: Design end-to-end solutions architecture that aligns with the organization’s digital transformation vision. Develop detailed technical designs, ensuring scalability, security, and integration with existing systems.

1. Machine Learning and AI Expertise: Provide in-depth expertise in Machine Learning, NLP, Generative AI, and other AI-related fields. Evaluate, select, and integrate relevant AI technologies to enhance healthcare processes, decision-making, and patient care.

1. Project Management: Lead the planning, execution, and delivery of digital transformation projects. Manage project timelines, resources, and risks to ensure successful deployment and implementation of AI solutions.

1. Healthcare Domain Knowledge: Leverage your extensive healthcare industry knowledge to understand regulatory requirements, compliance standards, and patient privacy concerns. Translate healthcare challenges into actionable technology solutions.

1. Collaboration: Work closely with cross-functional teams, including Data Scientists, Data Engineers, Software Developers, and healthcare domain experts. Foster a collaborative and innovative environment to achieve project goals.

1. Technical Evaluation: Evaluate emerging AI technologies, tools, and frameworks relevant to healthcare applications. Recommend and implement improvements to existing solutions to enhance performance and efficiency.

1. Documentation: Prepare comprehensive technical documentation, including architecture diagrams, design specifications, and implementation guidelines

Additional Responsibilities:

1.    Conversational AI Design: Lead the design and implementation of Conversational AI solutions, including chatbots and virtual assistants, to enhance user interactions and improve customer experiences in the healthcare domain

2.    Intelligent Document Processing: Architect solutions for Intelligent Document Processing (IDP) to automate the extraction of information from unstructured documents, such as medical records, reports, and forms.

3.    Proof of Concept (PoC) Development: Lead the development of PoCs to demonstrate the feasibility and potential of AI technologies in addressing specific healthcare challenges. Collaborate with stakeholders to gather feedback and iterate on the PoC to validate its efficacy

4.    Industry Trends and Innovation: Stay abreast of the latest trends and advancements in Machine Learning, NLP, Generative AI, and healthcare technology. Propose innovative solutions to address emerging challenges and opportunities

5.    Stakeholder Education: Educate and collaborate with key stakeholders, including executives, project sponsors, and healthcare professionals, to build awareness and understanding of AI technologies’ potential impact on healthcare processes and patient outcomes

Clinical Decision Support: Collaborate with healthcare professionals and data scientists to design and deploy AI-powered clinical decision support systems, assisting medical staff in diagnosing and treating patients

 Skills Technical Skills

• Machine Learning: Strong proficiency in designing and implementing machine learning models, including supervised and unsupervised learning techniques, regression, classification, and clustering algorithms.
• Natural Language Processing (NLP): In-depth knowledge of NLP techniques, such as text preprocessing, tokenization, word embeddings, sentiment analysis, entity recognition, and topic modeling.
• Conversational AI: Hands-on experience in developing and deploying conversational AI applications, including chatbots and virtual assistants, using frameworks such as Dialogflow, Rasa, or Microsoft Bot Framework.
• Generative AI: Expertise in Generative AI models, such as GANs (Generative Adversarial Networks) or VAEs (Variational Autoencoders), and their applications in generating realistic and creative content.
• Intelligent Document Processing: Proficiency in implementing Intelligent Document Processing solutions, including OCR (Optical Character Recognition) and information extraction techniques for unstructured data.
• Deep Learning: Familiarity with deep learning architectures, such as CNNs (Convolutional Neural Networks), RNNs (Recurrent Neural Networks), and Transformers, and their applications in NLP and computer vision tasks.
• AI Frameworks: Experience with popular AI frameworks and libraries, such as TensorFlow, Keras, PyTorch, spaCy, and Hugging Face Transformers.
• Cloud Platforms: Knowledge of cloud platforms, such as AWS, Azure, or Google Cloud, for deploying and scaling AI applications in the cloud.
• Data Engineering: Proficiency in data engineering principles and tools for data preprocessing, data integration, and data pipeline development to support AI model training and deployment.
• Data Privacy and Security: Understanding of data privacy regulations and best practices for ensuring data security in AI-driven applications, especially in healthcare environments.
• Model Deployment: Experience in deploying AI models in production environments using APIs, containers, or edge computing, ensuring scalability and efficiency.
• Model Explainability: Knowledge of techniques for model explainability and interpretability to address the “black-box” nature of AI models and enhance transparency.
• AI Governance: Familiarity with AI governance principles and best practices to ensure responsible and ethical AI deployments.
• Software Development: Proficiency in software development methodologies and programming languages (e.g., Python, Java, or C++) for building AI-driven applications.
• Data Visualization: Skills in data visualization tools and libraries (e.g., Matplotlib, Plotly, or Tableau) to communicate AI insights effectively.
• Agile Methodology: Experience in working within Agile development environments to deliver AI solutions in iterative and incremental cycles
• Knowledge of Healthcare Regulations: Awareness of healthcare regulations and standards, including HIPAA, GDPR, and FDA guidelines, to ensure compliance in AI-driven healthcare applications
• AI DevOps: Knowledge of AI DevOps practices for automating model training, testing, and deployment processes, ensuring reproducibility and version control.
• Business Process Analysis: Proficiency in analyzing existing business processes to identify opportunities for automation and optimization through AI-driven solutions
• Process Automation: Experience in designing and implementing AI-based process automation solutions, such as Robotic Process Automation (RPA) and workflow automation
• Low-Code/No-Code AI Platforms: Experience in using low-code or no-code AI platforms to accelerate AI development and deployment processes
• Customer Journey Mapping: Proficiency in customer journey mapping to identify touchpoints for AI-driven personalization and customer experience enhancement

Soft Skills

• Communication Skills: Excellent verbal and written communication skills to effectively convey complex technical concepts to both technical and non-technical stakeholders.
• Problem-solving Ability: Strong analytical and problem-solving skills to identify business challenges and design innovative AI-driven solutions that address specific needs.
• Adaptability: Ability to adapt to rapidly changing technology trends and industry demands in the fast-paced landscape of digital transformation and AI technologies.
• Collaboration: Proven track record of collaborating with cross-functional teams, including Data Scientists, Software Engineers, and business stakeholders, to achieve common objectives.
• Leadership: Demonstrated leadership abilities to guide and inspire teams during AI project development, fostering a culture of innovation and continuous improvement.
• Creativity: Creative thinking to explore unconventional approaches and solutions in leveraging AI technologies for digital transformation endeavors.
• Strategic Thinking: Strategic mindset to align AI initiatives with the organization’s overall digital transformation strategy and long-term goals.
• Problem Framing: Skill in framing business problems and understanding user requirements to tailor AI solutions that deliver tangible value
• Continuous Learning: Eagerness to stay updated with the latest advancements in AI technologies and continuously improve skills through self-directed learning
• Presentation Skills: Ability to deliver engaging and persuasive presentations, communicating the value of AI solutions to executive leadership and stakeholders.
• Critical Thinking: Strong critical thinking skills to evaluate AI solutions, anticipate potential challenges, and make data-driven decisions during digital transformation projects.
• Business Acumen: Business acumen to grasp the organization’s industry dynamics, challenges, and opportunities, aligning AI initiatives with broader business strategies.
• Accountability: Sense of accountability for project outcomes and meeting project deadlines, taking ownership of successful AI solution delivery

  Work Experience Requirements

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field
• Solid understanding of cloud-based architectures, such as AWS, Azure, or Google Cloud, and experience with deploying AI models on cloud platforms.
• Significant experience in the healthcare domain, working on projects related to healthcare data analysis, predictive modeling, clinical decision support, or similar
• Project management certifications (e.g., PMP) or experience working in a project management framework
• Extensive experience (minimum 8 years) in designing, deploying, and maintaining Conversational AI solutions, preferably in the healthcare or related industries.
• Proven expertise in developing NLU models, language understanding pipelines, and intent recognition systems for Conversational AI applications.
• Hands-on experience in implementing Intelligent Document Processing (IDP) solutions, including OCR (Optical Character Recognition) and entity extraction.
• Proficiency in working with Conversational AI platforms and tools, such as Dialogflow, Rasa, Microsoft Bot Framework, or similar.
• Knowledge of advanced NLP techniques, including sentiment analysis, language translation, and topic modeling, to enhance Conversational AI interactions.
• Familiarity with popular NLP libraries and frameworks, such as NLTK, spaCy, transformers, and BERT.
• Experience in working with cloud-based AI services, such as Amazon Lex, Azure Bot Service, or Google Cloud Natural Language API.
• Strong understanding of microservices architecture and containerization technologies (e.g., Docker) for deploying AI solutions.
• Demonstrated ability to lead AI development teams and provide technical guidance in the deployment of Conversational AI and IDP projects

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Company Description

Company Info

• Industry: Call Center/IT-Enabled Services/BPO
• Company Size: 2001 - 5000 Employees
• Average Processing Time: 14 days
• Benefits & Others: Dental, Miscellaneous allowance, Medical, Sports (e.g. Gym), Corporate, Business Casual, Graveyard, Nighshift