AI Automation Business Consultant
Quick Summary
accuracy against the PDD, security and scalabi
Greenlight helps organizations solve complex business challenges through intelligent automation, agentic AI, and custom technology solutions. Our teams work directly with clients to understand their operations, identify opportunities, and rapidly build solutions that create measurable business value. We combine deep consulting expertise with hands-on engineering to bridge the gap between strategy and execution.
We're building a future where consultants and engineers work alongside AI to deliver faster outcomes, stronger businesses, and transformative customer experiences. We build with AI as a core delivery tool — Anthropic's Claude powers our discovery synthesis, analysis & design generation, and prompt engineering workflows, and this role sits at the center of that capability.
- Inherently inquisitive and driven — you want to know how everything works
- Fluent in both business and technology — you translate between worlds effortlessly
- Passionate about AI and automation — you stay ahead of the curve because it excites you
- Outstanding communicator — in the room with a CFO or a developer, you are equally at home
- Ownership mindset — you do not wait to be told; you move
The Automation Business Consultant is Greenlight’s connective tissue between client problems and automation solutions - equal parts discovery expert, AI prompt architect, pre-sales solutions contributor, and delivery quality anchor. You will work directly with clients in their environments - facilitating process workshops, uncovering automation opportunities, shaping AI agent logic, and producing the specifications that our RPA engineers and FDEs build against.
You will contribute to solution design and proposals, and own a disproportionate share of what determines whether a project is scoped correctly and delivers on time.
This role is purpose-built for someone mid-career who is technically sharp, client-confident, and ready to operate at the intersection of automation delivery and AI consulting. As the Automation Business Consultant, you are accountable for 2-3 engagements at a given time and are the intelligence and documentation layer that makes the rest of the pod move.
Director, Project Delivery & Strategy
RPA Engineers, FDEs, Solution Architects, Pre-Sales
Executive sponsors, process SMEs, solution stakeholders, vendor partners
Requirements
~1 min readRegular client travel required (onsite discovery, workshops, pre-sales)
UiPath, Microsoft Power Platform, Anthropic Claude / AI Agents
Mid-Career (4–8 years relevant experience)
Onshore Canada — Toronto preferred
Hybrid — onsite client-facing with occasional travel.
Responsibilities
~1 min read- Partner with the PM for client readiness activities pre project kickoff
- Lead process discovery workshops (onsite where required) running small builds in a single session and medium-to-large builds across three sessions with 1day Ai enabled PDD turnaround
- Produce PDDs within one day of completing discovery — the authoritative build specification, zero ambiguity, zero gaps
- Validate and refine AI-generated SDDs: accuracy against the PDD, security and scalability considerations confirmed and finalized with the engineer before build begins — without letting documentation block development
- Facilitate sprint demos with the client at the close of each Build sprint
- Begin test case development with the client in Week 1 of the build phase — in parallel with development, not after it — so UAT is ready to execute the moment a build is promotable
- Coordinate UAT execution: prepare client testers, manage the schedule, triage defects, and drive closure before go-live
- Where required, lead DU training during enablement and generate SOPs and change management materials where needed to close the gap between what was built and how the business will run it
- Translate business problems into prompt architecture for Claude and other LLM components - defining reasoning logic, decision trees, fallback paths, output format specifications, and human-in-the-loop triggers
- Specify output requirements in full — JSON schemas, response templates, validation rules — so developers integrate without guesswork
- Design and run LLM output evaluation frameworks: pass/fail criteria for probabilistic responses, regression testing when prompts or models change, and output drift monitoring before issues reach the client
- Maintain a prompt changelog and contribute to a shared testing library that raises quality standards across the practice
- Translate pre-sales discovery outputs into solution narratives: what the automation or AI agent will do, what it will replace, and what the business outcome looks like in concrete terms
- Own the solution definition layer - translating what a client needs into a scope that the delivery team can execute against cleanly, with no interpretation required
- Build reusable solution accelerators, discovery templates, and capability narratives that shorten the cycle on repeat opportunity types
- Build trust with process owners and SMEs fast — you need the real detail, not the version they think you want
- Stay active through the build: respond to developer queries quickly, flag scope and stakeholder risks the moment they surface, and keep the delivery thread tight
- Present documentation, agent specs, and UAT outcomes for client sign-off — clearly, confidently, no ambiguity
- Recognize and flag scope change triggers during build; partner with the PM to initiate CR process before absorbing out-of-scope requests.
- 4–8 years in a AI or Automation Consultant, or Technical Consulting role within technology
- Proven experience facilitating client-facing process discovery and requirements workshops (in-person and remote) and translating outputs into formal documentation
- Ability to produce structured requirements and process documentation: PDDs, BRDs, user stories, agent specs, test plans & test cases or equivalent deliverables built for an engineering team to execute against
- Hands-on experience with RPA platforms (UiPath strongly preferred) or AI/LLM-powered automation
- Direct exposure to AI tools, LLM APIs, or prompt engineering (formal role or through active self-taught)
- Experience contributing to scoping, solution design, or proposal activities - understanding how a solution gets defined before it gets built
- Anthropic Claude API, OpenAI API, or similar LLM interfaces: prompt design, output evaluation, and integration logic
Nice to have:
- Jira, Confluence, Azure DevOps, or equivalent for backlog management and documentation
- UiPath Business Analyst, Platform Associate, or Solution Architect certification
- Anthropic or other LLM platform certifications or formal prompt engineering training
- Blackbelt, CBAP, CCBA, IIBA, or equivalent BA certification
- Background in a consulting, managed services, or systems integrator environment (boutique preferred)
- Background in technical scoping, solution engineering, or client-facing advisory
- Precision and attention to detail — your documentation is what gets built; ambiguity costs the project
- Strong facilitation — Run structured workshops, control the room, and surface the detail that matters
- Technical fluency — comfortable enough with APIs, JSON, and automation logic to design agent workflows, not just describe them
- Analytical mindset — Deconstruct complex processes, define decision logic, and anticipate failure modes
- Client-confident communicator — executive presence, ability to go deep on technical detail
- Self-directed/fast-moving — comfortable in short-cycle delivery where not everything is defined upfront
- Travel-ready — this role includes regular client-site travel; you treat that as an advantage, not a burden
Before they walk into a discovery session, the best consultants already know the client industry, their competitive pressures, the systems they run, and where the operational pain typically lives in that sector. They speak the client language before the client has to explain it. They ask the question that reveals the real problem (not the one on the agenda). They leave the room with enough to write the PDD and design the agent logic, because they understood the business, not just the process. When something is ambiguous during the build, they surface it fast. They do not disappear into it. That combination (deep domain instinct and clean execution discipline) is what we are hiring for.
We use AI tools to support parts of our recruitment — things like organizing applications and flagging relevant experience. These tools inform our process, they don't drive it. Every hiring decision is made by our team, full stop.
Great Place to Work™
Greenlight is a certified Great Place to Work™ — 98% score. We're proud of that and we work every day to keep earning it.
Location & Eligibility
Listing Details
- Posted
- June 23, 2026
- First seen
- June 23, 2026
- Last seen
- June 23, 2026
Posting Health
- Days active
- 0
- Repost count
- 0
- Trust Level
- 60%
- Scored at
- June 23, 2026
Signal breakdown
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