AI Solution Architect
Indexed description
In This Role, Your Responsibilities Will Be
- Design and deliver end-to-end AI and agentic solutions across data, models, orchestration, integrations, security, deployment, and operations.
- Translate business problems into clear technical architectures and delivery plans, including deciding when agentic AI is appropriate versus simpler automation.
- Prototype, develop, test, and harden solutions to production standards, ensuring reliability, scalability, observability, and cost control.
- Architect and implement multi-agent systems capable of planning, reasoning, and acting through tools and workflows.
- Design scalable agents that interact with enterprise systems using tools and services.
- Apply guardrails, safety controls, iteration limits, and human-in-the-loop mechanisms to ensure controlled and auditable agent behavior.
- Architect clean integrations with ERP and other complex enterprise platforms using APIs, events, and workflow orchestration.
- Collaborate with platform, security, and application teams to align solutions with enterprise constraints and policies.
- Define and maintain enterprise AI architecture standards, reference architectures, design patterns, and approved technology stacks.
- Establish governance checkpoints, including architecture reviews, security and responsible AI controls, and pre-go-live readiness.
- Build reusable CoE assets such as templates, checklists, decision trees, evaluation scorecards, and runbooks.
For This Role, You Will Need
- Proven hands-on experience building Generative AI and multi-agent solutions for complex business process automation.
- Strong understanding of agent evaluation beyond model accuracy, including task success, tool selection, and reasoning quality.
- Experience with AI Ops / Agent Ops, including monitoring behavior, cost, drift, and failure modes in production.
- 8-10 years of experience designing and building enterprise-scale systems, ideally involving ERP or similarly complex platforms.
- Strong experience with Cloud and SaaS architectures, including identity, security, networking, and deployment.
- Hands-on expertise with APIs, integration patterns, workflow orchestration, CI/CD, containerization, and infrastructure as code.
- Solid grounding in LLMs, embeddings, RAG patterns, vector search, prompt design, and evaluation methods.
- Experience with open-source AI and agent orchestration frameworks and production-grade observability tools.
- Strong software engineering discipline, including clean interfaces, testability, and versioning.
- Advanced English skills
- Bachelor's degree or equivalent experience in Computer Science, Software Engineering, or a related field.
- Experience defining and operating enterprise AI governance models, including architecture reviews and production readiness controls.
- A track record of building reusable enterprise assets that accelerate AI adoption across teams.
We recognize the importance of employee wellbeing. We prioritize providing competitive benefits plans, a variety of medical insurance plans, Employee Assistance Program, employee resource groups, recognition, and much more. Our culture offers flexible time off plans, vacation and holiday leave.
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