Accelerance
Overview
Job Summary: We are seeking a highly skilled and forward-thinking Senior Solutions Architect with deep expertise in cloud-native architectures, extensive experience modernizing legacy systems and software, a strong track record in designing agentic AI and machine learning (ML) solutions, and hands-on experience delivering working software to join our Consulting team. In this dual pre-sales and delivery role, you will collaborate with business, engineering, and delivery leaders to design and de-risk modernization programs that combine AI acceleration with scalable, secure, and globally distributed execution. Your architectural leadership—spanning system and software design, ROI modeling, and governance implementation—will be instrumental in enabling clients to modernize confidently and deliver measurable outcomes through self-learning (AI-enabled) delivery models that continuously improve predictability and performance.
Responsibilities
Collaborate closely with clients to understand their business objectives, operational constraints, and data challenges, translating them into comprehensive solution designs that integrate AI/ML capabilities to enhance efficiency, decision-making, or user experience.
Design end-to-end architecture solutions for AI-augmented software applications, ML models, data pipelines, and analytics platforms, ensuring scalability, performance, resilience and security.
Lead the technical implementation effort, working closely with development teams, data engineers, ML scientists, and other stakeholders to ensure high-quality, on-time delivery of solutions.
Evaluate and recommend optimal software architectures, cloud services, AI frameworks, large language models (LLMs), vector databases, and orchestration platforms based on client needs and project goals.
Define and implement data integration and governance strategies to enable AI-ready infrastructure—including clean data ingestion, labeling, and secure interoperability across systems.
Develop and maintain architecture documentation, including system diagrams, ML model diagrams, data flow diagrams, design specifications, and technical documentation for reference and future use.
Conduct architecture and model reviews that include AI ethics, bias mitigation, and model governance best practices.
Develop accelerators, reusable components and reference architectures to enable faster delivery and standardization across engagements.
Stay current with emerging technologies, particularly in generative AI, agentic systems, and AI-native DevOps (AIOps), and incorporate relevant innovations into client architectures.
Provide technical leadership and mentorship to offshore teams, fostering a culture of innovation, collaboration, continuous learning, and continuous improvement across time zones.
Required Skills and Abilities
Strong strategic and analytical thinking, with the ability to balance big-picture vision and hands-on execution.
Deep understanding of AI/ML system design, data pipelines, and how AI overlays can enhance traditional SDLC and SaaS architectures.
Practical familiarity with generative AI platforms (e.g., OpenAI, Anthropic, Azure OpenAI Service), MLOps frameworks, and model lifecycle management.
Proven ability to translate business problems into AI-driven technical solutions that demonstrate measurable ROI, scalability, and risk reduction.
Understanding of prompt engineering, agentic workflows, and API-based integration of AI services within cloud and SaaS ecosystems.
Excellent communication and interpersonal skills, with the ability to engage effectively with executive stakeholders and inspire distributed engineering teams.
Comprehensive knowledge of technology consulting methods, including opportunity framing, solution shaping, and deal execution.
Thorough understanding of software development methodologies, delivery best practices, and estimation models.
Expertise in requirements, change, quality, and risk management processes within modern delivery frameworks.
Strong grasp of technology stack management, DevOps practices, and cross-platform integration.
Proficiency in content creation, documentation, and presentation tools to support pre-sales, architecture, and delivery governance.
Education and Experience
Bachelor's degree in Computer Science, Information Technology, or a related field; Master\'s degree preferred.
Relevant certifications such as AWS Certified Solutions Architect, Microsoft Certified: Azure Solutions Architect Expert, or equivalent cloud credentials highly desirable.
15+ years of progressive experience as a Technical or Solutions Architect, with recent, hands-on focus on AI-enabled software, data, cloud, and SaaS modernization.
Practical experience deploying AI/ML models in production environments, including vectorization, orchestration, and RAG-based data pipelines.
Expertise in software architecture principles, design patterns, and best practices for scalable, reliable, and secure systems.
Expertise in cloud computing concepts, architectures, and services (e.g., AWS, Azure, Google Cloud Platform), with proven ability to design cloud-native, multi-environment solutions.
Proficiency in integration design, including API-based orchestration, event-driven microservices, and secure data synchronization between platforms.
Familiarity with AI/LLM platforms including AWS Bedrock, Azure AI, Google Vertex AI, and LangChain or equivalent agentic frameworks.
Knowledge of big data technologies such as Hadoop, Spark, and Kafka considered a plus.
Demonstrated experience leading distributed, offshore, or nearshore delivery teams, ensuring architectural alignment, governance, and delivery excellence across geographies
About Accelerance Accelerance is the global leader in helping companies build and manage high-performing, distributed software development teams. We combine consulting expertise with a proven global partner network to help enterprises modernize legacy systems, scale innovation, and increase delivery reliability.
Our
AI-first consulting model
ensures that every engagement—whether in modernization, product engineering, or global team optimization—includes an intelligent automation or data-driven component.
We enable clients to achieve predictable results, cost efficiency, and organizational scalability through frameworks such as our OneShore™ model, Agile Factory Framework, and
Agentic Readiness Playbook.
Joining Accelerance means becoming part of a
globally distributed, AI-empowered
consulting team that values speed, accountability, and innovation.
Job Details
Seniority level: Mid-Senior level
Employment type: Full-time
Job function: Engineering and Information Technology
Referral notices and location-based postings have been removed for clarity.
#J-18808-Ljbffr
Job Summary: We are seeking a highly skilled and forward-thinking Senior Solutions Architect with deep expertise in cloud-native architectures, extensive experience modernizing legacy systems and software, a strong track record in designing agentic AI and machine learning (ML) solutions, and hands-on experience delivering working software to join our Consulting team. In this dual pre-sales and delivery role, you will collaborate with business, engineering, and delivery leaders to design and de-risk modernization programs that combine AI acceleration with scalable, secure, and globally distributed execution. Your architectural leadership—spanning system and software design, ROI modeling, and governance implementation—will be instrumental in enabling clients to modernize confidently and deliver measurable outcomes through self-learning (AI-enabled) delivery models that continuously improve predictability and performance.
Responsibilities
Collaborate closely with clients to understand their business objectives, operational constraints, and data challenges, translating them into comprehensive solution designs that integrate AI/ML capabilities to enhance efficiency, decision-making, or user experience.
Design end-to-end architecture solutions for AI-augmented software applications, ML models, data pipelines, and analytics platforms, ensuring scalability, performance, resilience and security.
Lead the technical implementation effort, working closely with development teams, data engineers, ML scientists, and other stakeholders to ensure high-quality, on-time delivery of solutions.
Evaluate and recommend optimal software architectures, cloud services, AI frameworks, large language models (LLMs), vector databases, and orchestration platforms based on client needs and project goals.
Define and implement data integration and governance strategies to enable AI-ready infrastructure—including clean data ingestion, labeling, and secure interoperability across systems.
Develop and maintain architecture documentation, including system diagrams, ML model diagrams, data flow diagrams, design specifications, and technical documentation for reference and future use.
Conduct architecture and model reviews that include AI ethics, bias mitigation, and model governance best practices.
Develop accelerators, reusable components and reference architectures to enable faster delivery and standardization across engagements.
Stay current with emerging technologies, particularly in generative AI, agentic systems, and AI-native DevOps (AIOps), and incorporate relevant innovations into client architectures.
Provide technical leadership and mentorship to offshore teams, fostering a culture of innovation, collaboration, continuous learning, and continuous improvement across time zones.
Required Skills and Abilities
Strong strategic and analytical thinking, with the ability to balance big-picture vision and hands-on execution.
Deep understanding of AI/ML system design, data pipelines, and how AI overlays can enhance traditional SDLC and SaaS architectures.
Practical familiarity with generative AI platforms (e.g., OpenAI, Anthropic, Azure OpenAI Service), MLOps frameworks, and model lifecycle management.
Proven ability to translate business problems into AI-driven technical solutions that demonstrate measurable ROI, scalability, and risk reduction.
Understanding of prompt engineering, agentic workflows, and API-based integration of AI services within cloud and SaaS ecosystems.
Excellent communication and interpersonal skills, with the ability to engage effectively with executive stakeholders and inspire distributed engineering teams.
Comprehensive knowledge of technology consulting methods, including opportunity framing, solution shaping, and deal execution.
Thorough understanding of software development methodologies, delivery best practices, and estimation models.
Expertise in requirements, change, quality, and risk management processes within modern delivery frameworks.
Strong grasp of technology stack management, DevOps practices, and cross-platform integration.
Proficiency in content creation, documentation, and presentation tools to support pre-sales, architecture, and delivery governance.
Education and Experience
Bachelor's degree in Computer Science, Information Technology, or a related field; Master\'s degree preferred.
Relevant certifications such as AWS Certified Solutions Architect, Microsoft Certified: Azure Solutions Architect Expert, or equivalent cloud credentials highly desirable.
15+ years of progressive experience as a Technical or Solutions Architect, with recent, hands-on focus on AI-enabled software, data, cloud, and SaaS modernization.
Practical experience deploying AI/ML models in production environments, including vectorization, orchestration, and RAG-based data pipelines.
Expertise in software architecture principles, design patterns, and best practices for scalable, reliable, and secure systems.
Expertise in cloud computing concepts, architectures, and services (e.g., AWS, Azure, Google Cloud Platform), with proven ability to design cloud-native, multi-environment solutions.
Proficiency in integration design, including API-based orchestration, event-driven microservices, and secure data synchronization between platforms.
Familiarity with AI/LLM platforms including AWS Bedrock, Azure AI, Google Vertex AI, and LangChain or equivalent agentic frameworks.
Knowledge of big data technologies such as Hadoop, Spark, and Kafka considered a plus.
Demonstrated experience leading distributed, offshore, or nearshore delivery teams, ensuring architectural alignment, governance, and delivery excellence across geographies
About Accelerance Accelerance is the global leader in helping companies build and manage high-performing, distributed software development teams. We combine consulting expertise with a proven global partner network to help enterprises modernize legacy systems, scale innovation, and increase delivery reliability.
Our
AI-first consulting model
ensures that every engagement—whether in modernization, product engineering, or global team optimization—includes an intelligent automation or data-driven component.
We enable clients to achieve predictable results, cost efficiency, and organizational scalability through frameworks such as our OneShore™ model, Agile Factory Framework, and
Agentic Readiness Playbook.
Joining Accelerance means becoming part of a
globally distributed, AI-empowered
consulting team that values speed, accountability, and innovation.
Job Details
Seniority level: Mid-Senior level
Employment type: Full-time
Job function: Engineering and Information Technology
Referral notices and location-based postings have been removed for clarity.
#J-18808-Ljbffr