OverviewTRL Real Estate is seeking an AI Assessment & Implementation Strategy Consultant to support corporate clients across broader middle-market industries, including manufacturing, logistics, infrastructure, real estate, energy, and other operationally complex businesses.
This person will lead AI assessment engagements with client stakeholders, identify operational bottlenecks and automation opportunities, and develop executive-ready AI implementation strategy reports and technical blueprints. The ideal candidate combines strong client-facing consulting skills with the technical depth to evaluate practical AI use cases involving LLMs, RAG, workflow automation, AI agents, data architecture, and enterprise systems.
This is not primarily a coding role, but the right person must understand AI architecture and implementation paths well enough to ask the right technical questions, speak credibly with CIO / CTO stakeholders, and create actionable blueprints that can lead into MVP or production implementation projects.
This is an initial contract / fractional consulting opportunity, with potential to expand into a longer-term or full-time role as client demand grows.
Engagement Details- Type: Contract / fractional consulting to start
- Location: US-based remote
- Timeline: Immediate need
- Hours: Estimated at ~20 hours/week to start. Actual weekly commitment may vary based on number of active assessment engagements and consulting capacity
- Potential to expand into longer-term or full-time role based on performance and client volume
Key Responsibilities- Lead AI assessment engagements with corporate clients, including discovery sessions with C-suite leaders, CIOs / CTOs, operational stakeholders, and functional teams.
- Evaluate client workflows, systems, bottlenecks, data availability, and operational pain points to identify where AI-enabled solutions can create measurable value.
- Develop professional, executive-ready AI assessment reports and implementation blueprints within a typical three-week assessment timeline.
- Translate business problems into practical AI implementation opportunities, including workflow automation, AI agents, RAG-enabled knowledge systems, process optimization, and decision-support tools.
- Recommend phased implementation roadmaps, including MVP scope, technical requirements, expected business impact, risks, and required project team structure.
- Assess the feasibility of AI solutions based on data readiness, integration complexity, operational constraints, and enterprise technology environments.
- Lead client conversations directly on behalf of the company, while being able to answer technical questions from CIO / CTO and technical stakeholders.
- Partner with TRL leadership to determine when an assessment should lead into a larger MVP or production implementation project.
- Help define what technical resources may be needed for follow-on implementation, including AI engineers, solution architects, data engineers, backend engineers, and project managers.
- Ensure recommendations are grounded, accurate, and realistic - avoiding generic AI outputs, hallucinated recommendations, or overpromising around AI capabilities.
Ideal Background- Experience in AI strategy, AI transformation, management consulting, enterprise technology consulting, solutions architecture, or AI implementation advisory.
- Strong ability to conduct client discovery, synthesize complex business / operational inputs, and produce polished reports for executive audiences.
- Practical understanding of AI implementation concepts, including LLMs, RAG, LangChain or similar frameworks, AI agents, automation workflows, data pipelines, APIs, and enterprise system integration.
- Ability to assess operational processes and recommend realistic AI-enabled solutions based on business value, technical feasibility, and implementation complexity.
- Comfortable speaking with technical and non-technical stakeholders, including CIOs, CTOs, business leaders, operations teams, and engineering teams.
- Strong writing and documentation skills, with experience producing strategy reports, implementation roadmaps, executive summaries, technical briefs, or consulting deliverables.
- Experience with middle-market companies or operationally complex industries such as manufacturing, logistics, infrastructure, energy, or real estate is a plus.
- US-based, native or highly fluent English communication required.
Must-Have Skills- AI strategy / AI transformation consulting
- Client-facing discovery and stakeholder interviews
- C-suite / CIO / CTO-facing communication
- AI readiness / workflow assessment
- Executive-ready report writing
- Implementation blueprint and roadmap development
- Understanding of LLMs, RAG, AI agents, and workflow automation
- Technical literacy across enterprise systems, data, APIs, and software implementation
- Ability to translate business requirements into actionable AI solution concepts and follow-on MVP recommendations
Nice-to-Have Skills- Prior management consulting or technology consulting background
- Experience building AI assessment frameworks or AI implementation playbooks
- Experience with LangChain, LlamaIndex, CrewAI, OpenAI, Claude, or similar tools
- Experience scoping MVPs or technical implementation teams
- Experience with industrial, manufacturing, logistics, infrastructure, energy, or real estate clients
- Ability to support multiple assessment engagements in parallel
- Prior experience helping clients move from AI assessment into MVP build or production rollout
Success in This Role Looks LikeWithin the first few engagements, this person should be able to independently lead client discovery, identify AI implementation opportunities, produce high-quality assessment reports, and recommend practical next steps that can lead into larger MVP or implementation projects.
The right person will not simply summarize stakeholder input using AI tools. They will understand what they are recommending, why it matters, what is technically feasible, and what resources are required to turn the strategy into a working solution.
This person must be able to operate at both levels: communicating clearly with executive stakeholders while also developing a technically credible AI implementation blueprint.
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