AI Engineer Consultant

Senior AI Engineer Consultant

Location: Dallas, TX | Seattle, WA | Atlanta, GA | Chicago, IL | New York, NY

Work Arrangement: Hybrid, 3 days onsite per week when not traveling. Client travel varies by engagement.

Base Salary: $150,000–$180,000 + Potential Sign-On Bonus

Work Authorization: Must have existing U.S. work authorization. H-1B transfers and STEM OPT are not supported for 2026 hiring.

About the Company

We're partnering with a global technology and consulting organization that helps large enterprises modernize their technology, transform business operations, and implement emerging technologies.

The company is making significant investments in its U.S. AI engineering capabilities, particularly around Generative AI and Agentic AI. Its data and AI consulting practice combines software engineering, cloud technologies, advanced analytics, and AI governance to help enterprise clients move beyond experimentation and deploy secure, scalable AI solutions into production.

With continued investment in its U.S. delivery teams, particularly in Dallas and Seattle, the organization is expanding its ability to deliver sophisticated AI applications across a variety of enterprise environments.

About the Role

We're looking for a Senior AI Engineer Consultant to design, develop, and deploy enterprise-grade Generative AI and Agentic AI applications.

This is a hands-on engineering position focused on building end-to-end AI agents, multi-step workflows, LLM-powered applications, Retrieval-Augmented Generation (RAG) systems, and backend services that integrate with enterprise platforms and business applications.

You'll work across the full development lifecycle, from understanding client requirements and designing technical solutions to implementation, integration, testing, deployment, and production monitoring.

A major focus is developing AI systems that go beyond basic chatbots and document retrieval. These applications will interact with enterprise data, call external tools and APIs, coordinate complex workflows, and support automated business processes.

You'll also work directly with client stakeholders, architects, and engineering teams to translate business challenges into practical, production-ready AI solutions.

What You'll Do

Agentic AI & LLM Development

• Design, build, and deploy end-to-end AI agents and agentic applications.
• Develop multi-step agent workflows using orchestration frameworks such as LangGraph, LangChain, or comparable technologies.
• Implement tool and function calling to connect AI agents with enterprise APIs, databases, and business systems.
• Integrate LLMs into applications supporting business automation, enterprise knowledge retrieval, and decision support.
• Build reusable agent components, orchestration patterns, and AI engineering accelerators.

RAG & Enterprise AI Applications

• Design and implement RAG pipelines that connect LLMs with structured and unstructured enterprise data.
• Integrate vector databases, embeddings, semantic search, and knowledge retrieval capabilities.
• Improve retrieval relevance, response accuracy, grounding, and application performance.
• Develop AI applications that combine retrieval, agent orchestration, and enterprise workflow automation.

Backend Engineering & Production Deployment

• Develop backend services, APIs, inference pipelines, and integrations supporting AI applications.
• Deploy AI solutions into production using cloud platforms such as AWS, Azure, or GCP.
• Implement testing, monitoring, observability, error handling, and production reliability controls.
• Troubleshoot agent behavior, LLM outputs, retrieval systems, backend integrations, and production issues.
• Incorporate appropriate security, governance, responsible AI practices, and quality controls.

Technical Design & Client Collaboration

• Translate client business requirements into practical engineering solutions.
• Participate in technical design discussions and evaluate implementation approaches and architectural tradeoffs.
• Collaborate with solution architects, backend engineers, data engineers, and business stakeholders.
• Contribute to reusable technical frameworks, implementation patterns, and architecture documentation.

What We're Looking For

• 5–6+ years of software engineering or AI/ML engineering experience , with a strong hands-on development background.
• Demonstrated experience building AI agents and agentic applications end-to-end , including multi-step workflows and tool/function calling.
• Hands-on experience developing LLM-powered applications using orchestration frameworks such as LangGraph, LangChain, or comparable technologies.
• Experience implementing RAG systems , vector search, and retrieval pipelines.
• Strong backend engineering experience , including APIs, microservices, application integrations, and production software development.
• Experience deploying AI applications or backend services into production using AWS, Azure, GCP, or comparable cloud environments .
• Understanding of production monitoring, observability, security, governance, and application reliability.
• Ability to explain technical implementation decisions and demonstrate ownership of solutions from development through deployment.
• Experience translating business requirements into technical solutions and collaborating with technical and non-technical stakeholders.

Nice to Have

• Previous technology consulting or client-facing engineering experience.
• Experience developing AI agents that execute business workflows through enterprise integrations.
• Experience with multiple cloud platforms.
• Front-end or UI development experience.
• Advanced retrieval techniques such as hybrid search, reranking, and retrieval evaluation.
• Experience with LLM evaluation frameworks, AI observability, human-in-the-loop workflows, and guardrails.
• Experience creating reusable AI engineering frameworks, accelerators, or reference implementations.
• Experience delivering AI applications within complex or regulated enterprise environments.

Why This Role?

This opportunity offers the chance to work on enterprise AI initiatives where the focus is on building and deploying real applications, not simply creating proofs of concept .

You'll be directly involved in developing sophisticated agentic AI systems that interact with enterprise applications, automate workflows, and solve meaningful business challenges.

The role provides exposure to different client environments, cloud platforms, and AI use cases, alongside opportunities to contribute to reusable engineering patterns and technical accelerators.

With significant investment in expanding its U.S. AI engineering capabilities, the organization is building teams focused on delivering production-ready AI solutions at enterprise scale.

This position is particularly well suited to engineers who enjoy remaining hands-on, making technical decisions, and working directly with customers to turn complex business challenges into working software.

Location & Schedule

The position is available across five U.S. locations:

• Dallas, TX: Highest hiring priority
• Seattle, WA: High-priority growth market
• Atlanta, GA
• Chicago, IL
• New York, NY

The role follows a hybrid schedule requiring a minimum of 3 days onsite per week when not traveling.

As a client-facing consulting position, travel requirements depend on the assigned engagement. Some projects may involve weekly client travel, while others may require minimal or no travel.