What are the responsibilities and job description for the AI Search Engineer / AI Solutions Consultant – Go-to-Market Lead position at United Software Group Inc?
We’re Hiring: AI Search Engineer / AI Solutions Consultant – Go-to-Market Lead
Location: Remote (Texas, USA)
This role combining AI engineering, go-to-market strategy, and customer enablement.
You will act as the bridge between product, engineering, and business teams—helping drive AI adoption, agentic workflow integration, and enterprise-scale enablement programs.
If you enjoy building with AI while also teaching, enabling, and scaling adoption—this role is for you.
Key Responsibilities
AI Go-to-Market & Adoption
- Lead AI platform releases and rollout strategies
- Drive adoption across enterprise teams
- Define KPIs for AI usage, performance, and impact
- Translate technical capabilities into business-friendly guidance
AI Engineering & Solutions
- Build and support GenAI and agent-based systems
- Work with LLMs, RAG pipelines, and AI orchestration frameworks
- Support integration of AI workflows into enterprise systems
Customer Enablement
- Conduct workshops, training sessions, and office hours
- Create playbooks, documentation, and reusable AI frameworks
- Enable teams to adopt AI tools effectively at scale
Product & Strategy
- Gather user feedback and influence product roadmap
- Partner with engineering and product teams
- Provide executive-level insights and adoption metrics
Governance & Compliance
- Ensure responsible AI and security compliance
- Support audit and validation processes
Required Skills
- 4 years in AI/ML, AI consulting, or technical product roles
- Strong programming skills in Python and JavaScript/TypeScript
- Experience with GenAI, LLMs, or AI-driven solutions
- Strong communication and stakeholder management skills
- Ability to work in fast-paced, ambiguous environments
Preferred Skills
- Experience with OpenAI / Azure OpenAI / Hugging Face
- Familiarity with LangChain / LangGraph / vector databases
- Knowledge of RAG, agentic AI, and LLM workflows
- Cloud experience (Azure / AWS / GCP)
- MLOps / LLMOps exposure
- Experience in technical enablement or training programs