Solution Architect

ppWe are seeking an experienced, highly adaptable, curious, and fast?thinking AI Solutions Architect to design, prototype, and deliver innovative AI capabilities across internal use cases.The ideal candidate combines strong foundational understanding of AI/ML technologies with a proactive drive to stay ahead of industry advancements, especially in generative AI and emerging architectures./p pThis role bridges business needs and technical execution, architecting dynamic solutions that leverage LLMs, traditional ML, data pipelines, RAG, agents, and enterprise integrations./p h3CORE RESPONSIBILITIES /h3 h3Solution Architecture Innovation /h3 ul liTranslate business challenges into well?scoped AI solutions, balancing feasibility, value, cost, and speed./li liArchitect end?to?end AI systems, including data ingestion, model training, inference pipelines, monitoring, and governance./li liDesign and refine LLM/RAG architectures, agent workflows, and prompt engineering patterns./li liRapidly explore emerging tools/techniques to extend AI capabilities across the organization./li liBuild reusable reference architectures and best practices for internal teams./li /ul h3Technical Leadership Execution /h3 ul liPartner with engineering, data science, and product teams to guide implementation./li liConduct PoCs, prototypes, and pilots to validate technical suitability before scaling./li liEnsure solutions meet performance, security, compliance, and cost?efficiency requirements./li liIntegrate AI capabilities into existing systems, both cloud and legacy./li liWork with MLOps/DevOps to establish robust CI/CD, observability, and lifecycle management./li /ul h3Strategy, Governance Cross?Functional Collaboration /h3 ul liComplement the Product team by defining the technical AI/ML roadmap, assessing feasibility, shaping the use?case pipeline, and specifying the architecture required to deliver prioritized initiatives./li liProvide expertise on responsible AI, privacy, and risk?aware design./li liCommunicate complex concepts to stakeholders at all levels./li liMentor engineers and data scientists on architecture, quality, and emerging AI capabilities./li /ul h3QUALIFICATIONS /h3 h3Education /h3 ul liBachelor’s or Master’s degree in Computer Science, Engineering, or related field.OR equivalent work experience./li liAdditional certifications in AI/ML technologies are preferred./li /ul h3Technical Background /h3 ul li7+ years in solution architecture with proficiency in data architecture, including data pipelines, warehousing / Lakehouse concepts, APIs and integration patterns./li liStrong understanding of security, privacy, compliance, and responsible AI principles, including access control, data protection, and risk mitigation./li liDeep understanding of machine learning, generative AI, LLMs, RAG, prompt engineering, vector databases, and model evaluation frameworks./li liExperience translating business requirements into solution architectures, technical roadmaps, and implementation plans./li liExperience working cross?functionally with engineering, product, data teams, and business stakeholders to deliver measurable outcomes./li liKnowledge of MLOps/LLMOps practices such as CI/CD, model monitoring, observability, versioning, governance, and lifecycle management./li /ul h3Mindset Soft Skills /h3 ul liExceptionally curious, adaptive, and proactive, stays ahead of fast?changing AI technologies./li liFast learner with ability to shift between conceptual and hands?on tasks./li liStrong problem solver with a “builder” mentality./li liComfortable with ambiguity, rapid experimentation, and iterative design./li liExcellent communicator to both technical and business audiences./li liCollaborative and supportive partner to cross?functional teams./li /ul /p #J-*****-Ljbffr

li /ul h3QUALIFICATIONS /h3 h3Education /h3 ul liBachelor’s or Master’s degree in Computer Science, Engineering, or related field. OR equivalent work experience. /li liAdditional certifications in AI/ML technologies are preferred. /li /ul h3Technical Background /h3 ul li7+ years in solution architecture with proficiency in data architecture, including data pipelines, warehousing / Lakehouse concepts, APIs and integration patterns. /li liStrong understanding of security, privacy, compliance, and responsible AI principles, including access control, data protection, and risk mitigation. /li liDeep understanding of machine learning, generative AI, LLMs, RAG, prompt engineering, vector databases, and model evaluation frameworks. /li liExperience translating business requirements into solution architectures, technical roadmaps, and implementation plans. /li liExperience working cross?functionally with engineering, product, data teams, and business stakeholders to deliver measurable outcomes. /li liKnowledge of MLOps/LLMOps practices such as CI/CD, model monitoring, observability, versioning, governance, and lifecycle management. /li /ul h3Mindset Soft Skills /h3 ul liExceptionally curious, adaptive, and proactive, stays ahead of fast?changing AI technologies. /li liFast learner with ability to shift between conceptual and hands?on tasks. /li liStrong problem solver with a “builder” mentality. /li liComfortable with ambiguity, rapid experimentation, and iterative design. /li liExcellent communicator to both technical and business audiences. /li liCollaborative and supportive partner to cross?functional teams.