Senior AI Solution Architect
New
J
JobgetherEnterprise AI
Based in the United States; option to work remotely from the United StatesFull-TimeSenior
SalaryAnnual base salary ranging from $129,000 to $180,000, plus eligibility for an annual incentive.
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Job Details
- Experience
- At least 10 years of experience in software engineering or technical solution development.
- Required Skills
- PythonArtificial IntelligenceJavaMachine LearningSoftware EngineeringLLM
Requirements
- Have a bachelor's degree in Computer Science, Engineering, Data Science, or a related technical discipline, or equivalent professional experience.
- Have at least 10 years of experience in software engineering or technical solution development.
- Have experience building and deploying AI, machine learning, automation, or data-driven solutions in business or enterprise environments.
- Demonstrate strong programming skills and practical experience developing prototypes using Python, Java, or similar languages.
- Be able to translate business requirements into technical solutions in collaboration with stakeholders.
- Have experience taking solutions from concept through prototype development and validation.
- Be familiar with structured and unstructured data sources and their integration into technical solutions.
- Have experience managing several complex projects or initiatives concurrently.
- Demonstrate problem-framing, analytical thinking, and decision-making skills when requirements or priorities are unclear or evolving.
- Be able to connect technical decisions to measurable business outcomes and communicate their value.
- Demonstrate stakeholder management and communication skills with technical teams, business partners, and senior leadership.
- Bring business judgment to balance potential value, technical feasibility, scalability, and adoption.
Responsibilities
- Work with Marketplace, product, operations, and commercial teams to understand workflows, business processes, and operational challenges.
- Identify and prioritize AI and automation opportunities based on business value, feasibility, and scalability.
- Translate ambiguous business challenges into technical approaches, solution hypotheses, and development plans.
- Build and deploy prototypes and proof of concepts using enterprise data, internal platforms, and AI, machine learning, and large language model technologies.
- Test solutions against real-world workflows and data to demonstrate business impact.
- Collaborate with Technology and Data/AI teams to turn validated prototypes into production-ready solutions.
- Support implementation, adoption, and continuous improvement during rollouts and later iterations.
- Define and monitor indicators for operational efficiency, cost savings, revenue contribution, and user adoption.
- Contribute reusable frameworks, tools, and enterprise platform improvements, and mentor less experienced colleagues.
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