Senior Level AI Engineer Jobs
Senior level ai engineer jobs put experienced professionals in charge of model architecture, technical roadmaps, and the cross-functional teams that bring AI systems into production. Roles are concentrated across Technology & Software, Banking & Financial Services, and Electronics & Hardware, with a mix of on-site, remote, and hybrid settings, and employers like EY, Databricks, and Capital One 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.
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 & Software115
- Banking & Financial Services27
- Electronics & Hardware21
- Consulting & Professional Services20
- Investment & Asset Management12
Senior Level AI Engineer Jobs: Frequently Asked Questions
How do I get a senior level ai engineer job?
Employers hiring at this level look for candidates who have owned the full lifecycle of production AI systems, not just contributed to them. Demonstrating that you have set technical direction, resolved ambiguous problems at scale, and mentored junior engineers gives you a clear edge. A portfolio of shipped models and published or presentable work on complex architectures strengthens any application significantly.
Which companies hire senior level ai engineers?
Companies hiring senior level ai engineers right now include EY, Databricks, and Capital One, based on current listings on Migrate Mate as of September 2026. Hiring at this level comes from a wide range, including large technology firms, enterprise software companies, financial institutions, and well-funded startups building AI-first products.
Are there remote senior level ai engineer jobs?
Yes, remote and hybrid options are common at this level. About 45% of senior level ai engineer openings are remote or hybrid as of September 2026, reflecting how many organizations treat experienced AI engineers as distributed-first talent. On-site roles tend to concentrate in companies with sensitive data environments or hands-on hardware requirements.
What makes an ai engineer role senior level?
Senior level roles are defined by scope and ownership rather than task execution. At this stage, you are expected to design system architecture, set standards the team follows, drive decisions that affect product direction, and mentor engineers at earlier career stages. The problems are less defined, the tradeoffs are higher stakes, and the accountability for outcomes sits with you.
Which industries hire the most senior level ai engineers?
Senior level ai 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 because they are deploying AI at scale across core business functions, creating sustained demand for engineers who can lead that work rather than simply contribute to it.