EXL Service - Solutions Architect - Digital Transformation & Solutioning

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.

Responsibilities:

- 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

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.

2. 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.

3. 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.

4. 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.

5. 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.

Skills:

1. Machine Learning: Strong proficiency in designing and implementing machine learning models, includingsupervised and unsupervised learning techniques, regression, classification, and clustering algorithms.

2. Natural Language Processing (NLP): In-depth knowledge of NLP techniques, such as text preprocessing,tokenization, word embeddings, sentiment analysis, entity recognition, and topic modeling.

3. Conversational AI: Hands-on experience in developing and deploying conversational AI applications, includingchatbots and virtual assistants, using frameworks such as Dialogflow, Rasa, or Microsoft Bot Framework.

4. 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.

5. Intelligent Document Processing: Proficiency in implementing Intelligent Document Processing solutions,including OCR (Optical Character Recognition) and information extraction techniques for unstructured data.

6. 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.

7. 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 andscaling AI applications in the cloud.

8. 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.

9. Data Privacy and Security: Understanding of data privacy regulations and best practices for ensuring datasecurity in AI-driven applications, especially in healthcare environments.

10. Model Deployment: Experience in deploying AI models in production environments using APIs, containers, oredge computing, ensuring scalability and efficiency.

Technical Skills

1. Model Explainability: Knowledge of techniques for model explainability and interpretability to address the "black-box" nature of AI models and enhance transparency.

2. AI Governance: Familiarity with AI governance principles and best practices to ensure responsible and ethical AIdeployments.

3. Software Development: Proficiency in software development methodologies and programming languages (e.g.,Python, Java, or C++) for building AI-driven applications.

4. Data Visualization: Skills in data visualization tools and libraries (e.g., Matplotlib, Plotly, or Tableau) tocommunicate AI insights effectively.

5. Agile Methodology: Experience in working within Agile development environments to deliver AI solutions initerative and incremental cycles

6. Knowledge of Healthcare Regulations: Awareness of healthcare regulations and standards, including HIPAA,GDPR, and FDA guidelines, to ensure compliance in AI-driven healthcare applications

7. AI DevOps: Knowledge of AI DevOps practices for automating model training, testing, and deploymentprocesses, ensuring reproducibility and version control.

8. Business Process Analysis: Proficiency in analyzing existing business processes to identify opportunities forautomation and optimization through AI-driven solutions

9. Process Automation: Experience in designing and implementing AI-based process automation solutions, such asRobotic Process Automation (RPA) and workflow automation

10. Low-Code/No-Code AI Platforms: Experience in using low-code or no-code AI platforms to accelerate AIdevelopment and deployment processes

11. Customer Journey Mapping: Proficiency in customer journey mapping to identify touchpoints for AI-drivenpersonalization and customer experience enhancement

Soft Skills:

12. Communication Skills: Excellent verbal and written communication skills to effectively convey complex technicalconcepts to both technical and non-technical stakeholders.

13. Problem-solving Ability: Strong analytical and problem-solving skills to identify business challenges and designinnovative AI-driven solutions that address specific needs.

14. Adaptability: Ability to adapt to rapidly changing technology trends and industry demands in the fast-pacedlandscape of digital transformation and AI technologies.

15. Collaboration: Proven track record of collaborating with cross-functional teams, including Data Scientists,Software Engineers, and business stakeholders, to achieve common objectives.

16. Leadership: Demonstrated leadership abilities to guide and inspire teams during AI project development,fostering a culture of innovation and continuous improvement.

17. Creativity: Creative thinking to explore unconventional approaches and solutions in leveraging AI technologies

Work Experience Requirements:

1. Bachelor's or Master's degree in Computer Science, Engineering, or a related field

2. Solid understanding of cloud-based architectures, such as AWS, Azure, or Google Cloud, and experience with deploying AI models on cloudplatforms.

3. Significant experience in the healthcare domain, working on projects related to healthcare data analysis, predictive modeling, clinicaldecision support, or similar

4. Project management certifications (e.g., PMP) or experience working in a project management framework

5. Extensive experience (minimum 8 years) in designing, deploying, and maintaining Conversational AI solutions, preferably in the healthcareor related industries.

6. Proven expertise in developing NLU models, language understanding pipelines, and intent recognition systems for Conversational AIapplications.

7. Hands-on experience in implementing Intelligent Document Processing (IDP) solutions, including OCR (Optical Character Recognition) andentity extraction.

8. Proficiency in working with Conversational AI platforms and tools, such as Dialogflow, Rasa, Microsoft Bot Framework, or similar.

9. Knowledge of advanced NLP techniques, including sentiment analysis, language translation, and topic modeling, to enhance ConversationalAI interactions.

10. Familiarity with popular NLP libraries and frameworks, such as NLTK, spaCy, transformers, and BERT.

11. Experience in working with cloud-based AI services, such as Amazon Lex, Azure Bot Service, or Google Cloud Natural Language API.

12. Strong understanding of microservices architecture and containerization technologies (e.g., Docker) for deploying AI solutions.

13. Demonstrated ability to lead AI development teams and provide technical guidance in the deployment of Conversational AI and IDP projects