Senior Level AI Solutions Engineer Jobs
Senior level ai solutions engineer jobs place experienced professionals in charge of enterprise AI architecture, client outcome ownership, and the cross-functional teams that deliver production solutions. Roles concentrate across Technology & Software, Banking & Financial Services, and Electronics & Hardware, with a mix of on-site, remote, and hybrid settings, and employers like NVIDIA, Gartner, and Capgemini hiring at this level now.
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Location: United States (Remote)
Work Hours: 8:00 AM – 5:00 PM Pacific Time (Strict & Non-Negotiable)
Role Overview
We are seeking a production-focused Senior AI Solutions Engineer based in US to architect, build, and scale high-impact AI workflows, agentic automation, and internal tooling within our enterprise production systems. In this role, you will bridge the gap between high-level business strategy and hands-on engineering execution. You will work directly with business stakeholders to clarify ambiguous requirements, design robust solution architectures around Claude and enterprise LLM APIs, and embed AI capabilities into existing, complex codebases.
Key Responsibilities
- End-to-End Solution Ownership: Take loosely defined business problems and drive them from early architectural design through to deployment and rapid iteration.
- Architectural Leadership: Design scalable AI applications, copilots, workflow automations, and agentic pipelines integrated into multi-language enterprise applications.
- Cross-Functional Alignment: Collaborate closely with non-technical business partners and technical peers to validate requirements, ask probing questions upfront, and align on clear technical roadmaps.
- Production Integration: Step into established, non-greenfield codebases to modify, extend, and embed AI APIs and automation tooling without requiring complete architecture handoffs.
- Constructive Collaboration: Actively challenge assumptions when requirements are inefficient or unclear, presenting well-reasoned technical alternatives to keep teams moving forward.
Key Requirements
1. Communication & Autonomy
- Direct & Concise Communication: Strong written and verbal communication skills. Ability to explain technical trade-offs clearly to both engineering peers and business partners without unnecessary complexity.
- Self-Directed Problem Solver: High degree of autonomy. Able to navigate ambiguity, drive alignment across delivery teams, and own outcomes end-to-end.
2. Technical & AI Ecosystem
- GenAI & Solution Architecture: 2+ years designing and delivering enterprise AI/GenAI solutions, backed by 10+ years of software engineering experience, including scalable architecture, API integration, security, observability, and production deployment.
- Claude Experience (Mandatory): Proven hands-on experience designing, developing, and shipping production solutions using Claude and Claude APIs, including tool/function calling, structured outputs, prompt/context management, and enterprise integration patterns.
- Agentic AI & Multi-Agent Systems: Strong experience designing agentic and multi-agent architectures, including agent orchestration, supervisor/worker patterns, task decomposition, agent-to-agent communication, dynamic routing, shared/isolated state, memory management, human-in-the-loop workflows, retries, guardrails, and failure handling.
- AI Tooling & Frameworks: Deep hands-on experience with Python, RAG, Vector Databases, embeddings, semantic/hybrid search, prompt pipelines, and context engineering, using frameworks/protocols such as LangGraph, LangChain, and MCP.
- Agent Orchestration & Tool Integration: Experience building agents that securely interact with APIs, databases, enterprise systems, search/RAG services, and MCP tools, with stateful workflow execution, checkpointing, structured tool invocation, and authorization controls.
- AI Evaluation & Observability: Experience implementing LLM/agent evaluation, tracing, monitoring, hallucination/groundedness checks, token and latency optimization, cost monitoring, and agent/tool-call debugging for production AI systems.
- Core Stack Expertise: Working knowledge of at least one core technology stack—React, JavaScript/TypeScript, Java, or .NET—to enable rapid onboarding and integration with existing production systems.
3. Availability
- Strict PST Schedule: Must be fully available and responsive during business hours (8:00 AM – 5:00 PM Pacific Time, Monday–Friday).
Preferred Qualifications / Pluses
- Retail & Ecommerce Context: Familiarity with digital commerce workflows, AI-powered search, pricing, customer experience, or transactional platform paradigms.
- Internal Platform Tooling: Experience delivering internal automation, operational tools, or developer platforms at enterprise scale.
- Azure / Enterprise Cloud: Hands-on experience with Azure OpenAI or multi-cloud platform integrations.
About VRIZE
VRIZE is a global digital engineering and technology consulting company that partners with leading enterprise organizations to accelerate digital transformation through AI, cloud, data, and modern software engineering. Our teams specialize in delivering innovative, scalable solutions across industries including retail, financial services, healthcare, manufacturing, and technology. At VRIZE, you'll work alongside experienced engineers, architects, and business leaders to design and implement cutting-edge AI solutions that solve complex business challenges. We foster a collaborative, innovation-driven environment where continuous learning, technical excellence, and customer success are at the core of everything we do.
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Who's Hiring



Top Industries Hiring
- Technology & Software22
- Banking & Financial Services6
- Electronics & Hardware5
- Healthcare & Medical Services3
- Investment & Asset Management3
Senior Level AI Solutions Engineer Jobs: Frequently Asked Questions
How do I get a senior level ai solutions engineer job?
Employers at this level look for candidates who have led end-to-end AI solution deployments, not just contributed to them. A strong portfolio demonstrating ownership of architecture decisions, measurable client outcomes, and the ability to translate complex AI capabilities into business value is essential. Experience mentoring engineers and influencing technical roadmaps gives candidates a clear edge over those with equivalent years but narrower scope.
Which companies hire senior level ai solutions engineers?
Companies hiring senior level ai solutions engineers right now include NVIDIA, Gartner, and Capgemini, based on current listings on Migrate Mate as of September 2026. Hiring at this level comes primarily from large technology firms, cloud platform providers, and enterprise software companies building out dedicated AI practice teams.
Are there remote senior level ai solutions engineer jobs?
Yes, though availability varies by employer and client engagement model. About 43% of senior level ai solutions engineer openings are remote or hybrid as of September 2026, reflecting the field's strong acceptance of distributed technical work. Client-facing roles may still require periodic on-site presence, so it is worth reviewing each posting for travel expectations.
What makes an ai solutions engineer role senior level?
Senior level roles are defined by ownership rather than execution. At this stage, engineers are expected to define solution architecture independently, lead discovery and scoping with enterprise clients, and set technical direction for delivery teams. Mentoring junior and mid-level engineers is a standard expectation, and success is measured by client outcomes and platform adoption, not individual task completion.
Which industries hire the most senior level ai solutions engineers?
Senior level ai solutions engineer roles concentrate in Technology & Software, Banking & Financial Services, and Electronics & Hardware, based on current listings on Migrate Mate as of September 2026. These sectors drive hiring at this level because they are actively scaling AI-powered products and workflows that require experienced engineers who can own the full solution lifecycle from design through deployment.