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AI Solution Partner
Location
United States
Posted
100 days ago
Salary
0
Seniority
Junior
Job Description
AI Solution Partner
A.Team
• Join sales calls as the senior technical voice, establishing credibility with both technical and business stakeholders • Lead structured discovery to surface AI use-case opportunities, pain points, and value hypotheses • Facilitate working sessions to explore client data, systems, and operational context • Challenge and refine client assumptions where necessary to avoid misaligned scope • Translate discovery findings into coherent AI solution concepts, selecting appropriate architectures (agentic systems, RAG pipelines, data platforms, LLM integrations, etc.) • Design high-level solution architectures grounded in A.Team's composable AI platform capabilities • Define integration patterns with client systems (CRMs, ERPs, data warehouses, cloud infrastructure) • Identify and mitigate technical risk within proposed solutions • Author the technical sections of client proposals: solution overview, architecture diagrams, delivery approach, and assumptions • Produce delivery roadmaps with phased milestones and realistic timelines • Define resource requirements (roles, skills, FTE/day estimates) and translate into cost models • Work with the Account Executive to align technical scope with commercial packaging • Prepare and deliver tailored demonstrations of A.Team's AI platform and prior delivery examples • Adapt showcases to the client's industry, use case, and technical maturity • Build lightweight proof-of-concept assets where needed to accelerate client confidence • Articulate A.Team's differentiated AI proposition in terms relevant to the client's context • Stay current on the AI landscape (model capabilities, tooling, agent frameworks, enterprise deployment patterns) to advise credibly • Contribute to A.Team's internal IP: reusable solution patterns, reference architectures, and proposal templates.
Job Requirements
- Hands-on experience designing and delivering AI/ML systems in enterprise contexts
- Working knowledge of LLM application patterns: RAG, agentic orchestration, fine-tuning trade-offs, prompt engineering
- Familiarity with modern data and cloud infrastructure (AWS/GCP/Azure, data pipelines, APIs)
- Able to produce architecture diagrams and technical documentation to a professional standard
- Comfortable discussing trade-offs at both architecture and implementation level
- Natural in client-facing settings — can lead a discovery session, hold a room, and ask the right questions
- Able to translate ambiguous client problems into structured solution hypotheses
- Skilled at scoping — knows how to bound a problem, define assumptions, and manage expectation
- Comfortable working in ambiguity without over-engineering too early
- Understands how solution decisions affect cost, timeline, and risk
- Can contribute to or independently produce effort estimates and cost models
- Aware of how proposals are structured commercially and can align technical content accordingly
- Writes clearly and concisely — proposals, architecture docs, and async communications
- Can present confidently to mixed audiences (technical leads, CMOs, ops directors)
- Bridges language between engineering teams and business stakeholders.
Benefits
- Equal employment opportunities regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender, gender identity or expression, or veteran status.
- Proud to be an equal opportunity workplace.
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