AI Search Engineer

AI Search Engineer

Remote TEXAS USA

This is a remote engagement Artificial Intelligence Solutions Consultant – Go-to Market Lead

Team: Enterprise AI Platform / Digital Technology and Innovation

About This Role

Are you passionate about accelerating AI adoption, enabling engineering teams, and shaping how enterprise users build with emerging AI capabilities?

We are seeking a highly technical and business-savvy Artificial Intelligence Solutions Consultant who blends go-to-market strategy, forward-deployed engineering, and AI enablement. In this role, you will serve as the connective tissue between product, engineering, line-of-business stakeholders, and end users—helping teams adopt AI capabilities, integrate agentic workflows, and scale enablement into repeatable, self-service models.

Ideal candidates bring strong engineering fundamentals, deep customer empathy, and a teacher’s mindset—someone who enjoys building solutions, enabling others, and turning individual learnings into scalable programs and product improvements.

You’ll thrive here if you’re hands-on, fast-moving, and energized by dynamic environments where you both build and teach, deliver and scale.

Key Responsibilities

• Lead platform releases, feature rollouts, and adoption initiatives in partnership with product and engineering teams.
• Architect and execute go-to-market strategies spanning onboarding, training, documentation, and support.
• Own the rollout and adoption of new platform features and capabilities across stakeholder groups.
• Track KPIs such as adoption, reliability, latency, and business impact to guide continuous improvement.
• Translate platform updates into clear, actionable guidance for both technical and non-technical audiences.
• Lead interactive enablement programs—including live workshops, pair-programming sessions, office hours, and hands-on technical engagements.
• Help teams integrate AI tools and capabilities into day-to-day development practices.
• Create and maintain enablement materials, SDK resources, best practices, and repeatable playbooks.
• Scale individual training engagements into enterprise-wide digital learning content and self-service models.
• Build a deep understanding of customer pain points and workflows to tailor adoption strategies and reduce time-to-value.
• Establish tight feedback loops between end-users, product, and engineering teams—capturing insights that meaningfully inform roadmap decisions.
• Translate customer needs into product direction: define requirements, scope solutions, and influence implementation.
• Advocate for usability improvements and enhancements grounded in field observations and customer experience.
• Validate fixes, test new features, and conduct quality checks to proactively surface gaps in stability or performance.
• Maintain empathy for how developers work and champion features that improve the end-user experience.
• Build strong relationships with business stakeholders, end users, and product teams; serve as a trusted technical advisor.
• Communicate complex technical concepts clearly and with nuance across diverse audiences.
• Produce executive-ready updates, metrics, narratives, and adoption insights.
• Ensure alignment with model governance, responsible AI practices, data protection, and platform security controls.
• Contribute to documentation and artifacts for validation, testing, approvals, and audit readiness.
• Partner with risk, compliance, and security teams to ensure safe and compliant delivery of AI capabilities.

Required Qualifications

• Bachelor’s degree in a STEM field or equivalent hands-on experience.
• 4+ years of experience in all of the following: Artificial intelligence solutions, AI consulting, product/solution management, program delivery, or technical product ownership for AI/ML platforms—or equivalent experience delivering AI/ML outcomes at scale.

• Strong coding proficiency (Python, JavaScript/TypeScript, or similar)
• Proven ability to communicate complex technical topics to diverse audiences. Strong customer-service orientation and comfort facilitating interactive sessions and workshops.
• Demonstrated ability to learn and adapt quickly in ambiguous, fast-changing environments.
• Strong technical acumen with the ability to build deep relationships with engineering and business stakeholders. Customer empathy and a bias toward execution—quickly identifying solutions and advocating for improvements to meet user needs.

Desired Qualifications Education

• Master’s degree or higher in computer science, engineering, data science, or a related field.

Technical Expertise

• Hands-on experience developing or deploying GenAI or agentic AI systems (LLMs, RAG, tools/agents, orchestration frameworks).

• Familiarity with AI/ML platforms and cloud infrastructure (Azure, AWS, GCP).

• Experience with MLOps/LLMOps practices (model registry, CI/CD, evaluation, guardrails, monitoring).

• Proficiency with OpenAI, Azure OpenAI, Hugging Face, LangChain/LangGraph, vector databases, and related frameworks.

• Experience integrating LLM-powered workflows or agent-based systems into production environments.

Customer Enablement Experience

• Experience leading technical workshops, internal enablement programs, developer onboarding, or training initiatives.

• Background in product management, technical product ownership, customer success, or technical program delivery.

• Ability to distill complex topics into clear playbooks, documentation, and learning materials. Familiarity with collaboration and workflow tools such as Jira, Confluence, and ServiceNow.

Job Expectations

• Hybrid work schedule.

• Occasional travel for stakeholder workshops, training, and program reviews.