What are the responsibilities and job description for the Azure AI Solution Architect position at Jobs via Dice?
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The Senior Solutions Architect will primarily be responsible for architecting solutions for strategic initiatives and projects that combine new and existing applications, tools and technology to derive effective & efficient solutions that address the business problems/opportunities and also align to enterprise policies and standards.
This individual will also contribute to maturing Enterprise Architecture practice in the organization by providing patterns, guidelines, position papers as needed.
This role will focus on our Client's Artificial Intelligence (AI) Architecture to lead the architectural vision and implementation of Client's AI initiatives. The Expert AI Solutions Architect will not only design scalable, secure, and performant AI solutions but also dive deep into the code, prototype cutting-edge concepts, and guide their successful deployment.
Responsibilities
Deeply embed with our most strategic healthcare customers, serving as their technical thought partner in ideating and directly developing novel full-stack applications on our platform
Leverage your software engineering expertise in Python, Microsoft Azure and related software languages to create initial prototypes and contribute back durable product features.
Proactively provide guidance to our customers on how to maximize business impact from their applications, accelerating their time to value.
Forge and manage relationships with our customers' leadership and stakeholders to ensure their application's successful deployment and scale.
Collaborate closely with Virtusa internal and client teammates and cross-functional teams across the company to strategically drive our AI delivery towards exceeding customer expectations.
Define, design, and implement scalable, secure AI solutions leveraging Generative AI (e.g., LLMs, diffusion models), Agentic AI systems (e.g., multi-agent frameworks), and mature MLOps/LLMOps practices.
Architect and implement end-to-end AI workflows, including data ingestion pipelines, designing model orchestration layers, implementing prompt engineering strategies, deploying solutions and ensuring seamless integration with enterprise systems.
Develop and code robust frameworks for evaluating AI models - defining metrics, creating test cases, and implementing processes for accuracy, fairness, safety, and reliability, particularly for Generative and Agentic AI.
Lead the continuous integration and delivery (CI/CD) of AI models by developing automation scripts, configuring monitoring, establishing versioning, ensuring governance, and building scalable deployment pipelines.
Guide data scientists and ML engineers, offering hands-on assistance to ensure adherence to architectural principles and AI best practices.
Convert complex healthcare business challenges into actionable AI strategies, rapidly prototyping solutions to demonstrate feasibility and value.
Stay ahead of AI trends by evaluating new technologies, tools, and frameworks, conducting hands-on experiments and pilot projects to continuously enhance AI capabilities.
Establish AI governance policies, ensuring compliance with HIPAA, GDPR, ethical AI standards, model explainability, and internal security requirements.
Partner closely with product managers, business analysts, and data engineers to define requirements, document and deliver impactful AI solutions, and serve as the primary technical expert.
Maintain clear, comprehensive architectural documentation that includes implementation details.
This list is not all-inclusive and you are expected to perform other duties as requested or assigned.
Qualifications
Bachelor's or master's degree in computer science, AI, ML, Data Science, or a related quantitative field; Ph.D. is a plus.
7 years of experience in software architecture and engineering, with at least 2 years specializing in AI/ML, or demonstrable equivalent experience through significant, impactful AI/ML projects. Experience in medical insurance and/or healthcare preferred.
Expert proficiency in Python and hands-on experience with cloud AI/ML services (Azure preferred), including developing and deploying models.
Demonstrated ability to build and deploy Generative AI solutions (LLMs, diffusion models) with a strong portfolio or examples of hands-on work.
Familiarity with and ability to develop agentic AI frameworks such as LangChain, AutoGen, or similar, including custom agent development.
Expert knowledge of MLOps/LLMOps pipeline, including implementation with tools like MLflow, Kubeflow, Azure ML, or similar CI/CD platforms.
Proven ability working with prompt engineering techniques, large model attunement, and vector databases (e.g., Pinecone, Weaviate, Milvus).
Solid understanding of data privacy regulations (HIPAA, GDPR, CCPA).
Knowledge of and demonstrated ability in designing, developing, and integrating APIs for AI services.
Own outcomes end-to-end, and are willing to pick up whatever knowledge you're missing to get the job done to ensure both your team and our customers succeed.
Skilled communicator adept at explaining complex technical concepts to both technical and non-technical audiences with clarity and concision.
Led complex technical projects and programs with many stakeholders.
Have a humble attitude and an eagerness to help others with empathy.
Operate with high horsepower, are adept at frequent context switching and working on multiple projects at once with expansive ownership, and ruthlessly prioritize.
Thrive in dynamic environments and can navigate ambiguity with ease.
Influence and leadership skills, including the ability to influence cross-functional teams and stakeholders and effectively lead technical discussions and implementations.
Excellent verbal, written, and interpersonal communication skills.
Hands-on, practical experience delivering Microsoft's AI and cloud solutions, including AI Vision, AI language, AI Doc Intelligence, Azure Health Data Services, Azure OpenAI Service, Azure APIs, Azure Confidential Computing, Azure Machine Learning & Synapse Analytics.
Licenses
Microsoft Certified: Azure Solutions Architect, preferred.
AI/ML Certification, preferred.
- LOCAL PREFERRED********************
The Senior Solutions Architect will primarily be responsible for architecting solutions for strategic initiatives and projects that combine new and existing applications, tools and technology to derive effective & efficient solutions that address the business problems/opportunities and also align to enterprise policies and standards.
This individual will also contribute to maturing Enterprise Architecture practice in the organization by providing patterns, guidelines, position papers as needed.
This role will focus on our Client's Artificial Intelligence (AI) Architecture to lead the architectural vision and implementation of Client's AI initiatives. The Expert AI Solutions Architect will not only design scalable, secure, and performant AI solutions but also dive deep into the code, prototype cutting-edge concepts, and guide their successful deployment.
Responsibilities
Deeply embed with our most strategic healthcare customers, serving as their technical thought partner in ideating and directly developing novel full-stack applications on our platform
Leverage your software engineering expertise in Python, Microsoft Azure and related software languages to create initial prototypes and contribute back durable product features.
Proactively provide guidance to our customers on how to maximize business impact from their applications, accelerating their time to value.
Forge and manage relationships with our customers' leadership and stakeholders to ensure their application's successful deployment and scale.
Collaborate closely with Virtusa internal and client teammates and cross-functional teams across the company to strategically drive our AI delivery towards exceeding customer expectations.
Define, design, and implement scalable, secure AI solutions leveraging Generative AI (e.g., LLMs, diffusion models), Agentic AI systems (e.g., multi-agent frameworks), and mature MLOps/LLMOps practices.
Architect and implement end-to-end AI workflows, including data ingestion pipelines, designing model orchestration layers, implementing prompt engineering strategies, deploying solutions and ensuring seamless integration with enterprise systems.
Develop and code robust frameworks for evaluating AI models - defining metrics, creating test cases, and implementing processes for accuracy, fairness, safety, and reliability, particularly for Generative and Agentic AI.
Lead the continuous integration and delivery (CI/CD) of AI models by developing automation scripts, configuring monitoring, establishing versioning, ensuring governance, and building scalable deployment pipelines.
Guide data scientists and ML engineers, offering hands-on assistance to ensure adherence to architectural principles and AI best practices.
Convert complex healthcare business challenges into actionable AI strategies, rapidly prototyping solutions to demonstrate feasibility and value.
Stay ahead of AI trends by evaluating new technologies, tools, and frameworks, conducting hands-on experiments and pilot projects to continuously enhance AI capabilities.
Establish AI governance policies, ensuring compliance with HIPAA, GDPR, ethical AI standards, model explainability, and internal security requirements.
Partner closely with product managers, business analysts, and data engineers to define requirements, document and deliver impactful AI solutions, and serve as the primary technical expert.
Maintain clear, comprehensive architectural documentation that includes implementation details.
This list is not all-inclusive and you are expected to perform other duties as requested or assigned.
Qualifications
Bachelor's or master's degree in computer science, AI, ML, Data Science, or a related quantitative field; Ph.D. is a plus.
7 years of experience in software architecture and engineering, with at least 2 years specializing in AI/ML, or demonstrable equivalent experience through significant, impactful AI/ML projects. Experience in medical insurance and/or healthcare preferred.
Expert proficiency in Python and hands-on experience with cloud AI/ML services (Azure preferred), including developing and deploying models.
Demonstrated ability to build and deploy Generative AI solutions (LLMs, diffusion models) with a strong portfolio or examples of hands-on work.
Familiarity with and ability to develop agentic AI frameworks such as LangChain, AutoGen, or similar, including custom agent development.
Expert knowledge of MLOps/LLMOps pipeline, including implementation with tools like MLflow, Kubeflow, Azure ML, or similar CI/CD platforms.
Proven ability working with prompt engineering techniques, large model attunement, and vector databases (e.g., Pinecone, Weaviate, Milvus).
Solid understanding of data privacy regulations (HIPAA, GDPR, CCPA).
Knowledge of and demonstrated ability in designing, developing, and integrating APIs for AI services.
Own outcomes end-to-end, and are willing to pick up whatever knowledge you're missing to get the job done to ensure both your team and our customers succeed.
Skilled communicator adept at explaining complex technical concepts to both technical and non-technical audiences with clarity and concision.
Led complex technical projects and programs with many stakeholders.
Have a humble attitude and an eagerness to help others with empathy.
Operate with high horsepower, are adept at frequent context switching and working on multiple projects at once with expansive ownership, and ruthlessly prioritize.
Thrive in dynamic environments and can navigate ambiguity with ease.
Influence and leadership skills, including the ability to influence cross-functional teams and stakeholders and effectively lead technical discussions and implementations.
Excellent verbal, written, and interpersonal communication skills.
Hands-on, practical experience delivering Microsoft's AI and cloud solutions, including AI Vision, AI language, AI Doc Intelligence, Azure Health Data Services, Azure OpenAI Service, Azure APIs, Azure Confidential Computing, Azure Machine Learning & Synapse Analytics.
Licenses
Microsoft Certified: Azure Solutions Architect, preferred.
AI/ML Certification, preferred.
