Deployment Strategist
- Thỏa thuận
- Toàn thời gian
Hạn nộp hồ sơ: 11/10/2026 (Còn 28 ngày)
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Company Description
Lemi AI is on a mission to help enterprises build, control, and own their AI capabilities rather than depend on black-box solutions. The company is at an early stage, operating with a small, focused team that prioritizes deep technical challenges and long-term impact.
Joining
Lemi AI means working closely with founders and early teammates to shape core infrastructure, product direction, and engineering culture. This environment offers significant ownership, rapid learning, and the opportunity to influence how large organizations adopt and govern AI in practice.
Core Mission
Go inside our clients' organizations, find the problems that are actually worth solving with AI, and own those deployments from first conversation to running system. You are the person who decides what we build and why, and who the client calls when they want to know whether it is working.
This role exists because building the right thing matters more than building things fast. Enterprises rarely arrive with a well-specified AI problem. They arrive with a vague ambition, a political landscape, and a lot of processes nobody has examined closely in years. Your job is to go in, work out where AI would actually change the economics of how they operate, say no to the tempting-but-worthless ideas, and then carry the good ones all the way through to something running in production.
You are not a salesperson who hands off to engineering, and you are not a project manager tracking someone else's plan. You own the why and the what; our Founding Engineer owns the how. The two of you are a pair, and you will spend a lot of time in the same rooms.
🚀 Key Responsibilities
Part One: Use-Case Diagnosis
Find the Real Problem: Embed with client teams to map how work actually happens, not how the org chart says it happens. Identify where AI would materially change cost, speed, or quality, and quantify it well enough that a CFO would accept the number.
Prioritize Ruthlessly: Most AI ideas inside a large enterprise are not worth building. Your value is as much in what you talk clients out of as in what you talk them into.
Write the Brief: Turn a diagnosed opportunity into a scoped problem statement our engineers can build against, including success criteria agreed with the client before work starts.
Part Two: Deployment Ownership
Own It End-to-End: Carry each engagement from first scoping conversation through pilot, production, and adoption. You are accountable for whether the thing actually gets used, not just whether it shipped.
Navigate the Organization: Align stakeholders from operations staff to C-suite. Large enterprises kill good projects through inertia and internal politics far more often than through technical failure, and steering around that is your responsibility.
Drive Adoption: A deployed system nobody uses is a failed engagement. Train users, redesign workflows around the tool where needed, and stay close enough after launch to know whether behavior actually changed.
Report Honestly: Keep both the client and the founding team accurately informed on progress, risk, and value delivered. No sugar-coating in either direction.
Part Three: Commercial Growth
Expand from Delivered Value: The most durable growth comes from having done good work. Turn successful deployments into the next engagement, the next business unit, the next contract.
Shape How We Sell: We are pre-revenue and have no playbook yet. You will help define what we sell, how we price it, and how we scope engagements so they are profitable rather than open-ended.
Support New Business: Sit in on new client conversations as the person who can speak credibly about what is genuinely feasible, which is often the difference between winning a deal and overpromising into one.
🎯 Candidate Profile & Experience Requirements
5 to 10 Years in a Problem-Diagnosis Role: Management consulting (strategy or technology), enterprise solutions consulting, chief of staff at a fast-growing company, or senior operational ownership in an industry you know deeply. What matters is a track record of walking into an unstructured situation and leaving with a defensible answer.
Exceptional Communication Skills: You can hold a room of skeptical executives, explain a technical trade-off without jargon, and tell a client something they do not want to hear while keeping the relationship intact. Fluency in both English and Vietnamese is required, and we weigh this as heavily as analytical ability.
Technically Literate, Not Necessarily Technical: You do not need to write production code. You do need to understand what current AI systems can and cannot do well enough to avoid promising things that are not real, and to earn the respect of the engineers you work alongside. If you have shipped something technical yourself, that is a plus.
Commercial Instinct: Comfortable talking about money. You can build a business case, defend a price, and recognize when a deal is shaped badly for us before we sign it.
Comfort with Ambiguity: We are pre-product. There is no methodology to inherit and no deck template waiting for you. You will build those.
Enterprise or Conglomerate Experience (Strong Plus): Prior work with large conglomerates, state-owned enterprises, or regulated industries in Vietnam or the region. Understanding how decisions really get made inside these organizations is worth a great deal here.
🎁 What We Offer
Our team and advisors come from McKinsey, Deloitte, Visa, the World Bank, and the Asian Development Bank, alongside engineers who have shipped at Meta, Google, Tesla, and TikTok. You'll be working with people who understand both how large institutions make decisions and what can actually be built.
We're deliberately small, and we're aiming for a very big impact, which means an outsized share of that impact will trace back to the handful of people in this room, you included. We operate on radical transparency and assume best intention in each other: no corporate politics, no bureaucracy, and a lot of trust placed in your judgment.
Realistic Scope to Shape the Company: You are not joining a go-to-market function. You are creating one, and the way you choose to run engagements will become how this company works.
Direct Access to Decision-Makers, Ours and Theirs: No layers between you and our founders, and you will regularly be in front of client executives rather than briefing someone else who is.
Ground-Floor Equity Upside: Meaningful equity in exchange for being one of the first people in the building, anchoring a high-profile technology launch with a leading private, multi-industry conglomerate in Vietnam.
High-Caliber Peers: Work closely with a small team of experienced operators and engineers, several coming directly from top Silicon Valley companies.
Top-of-Market Compensation: We pay at the top of market for this role: base salary, equity, and healthcare, structured for an early-stage team.
Lemi AI is on a mission to help enterprises build, control, and own their AI capabilities rather than depend on black-box solutions. The company is at an early stage, operating with a small, focused team that prioritizes deep technical challenges and long-term impact.
Joining
Lemi AI means working closely with founders and early teammates to shape core infrastructure, product direction, and engineering culture. This environment offers significant ownership, rapid learning, and the opportunity to influence how large organizations adopt and govern AI in practice.
Core Mission
Go inside our clients' organizations, find the problems that are actually worth solving with AI, and own those deployments from first conversation to running system. You are the person who decides what we build and why, and who the client calls when they want to know whether it is working.
This role exists because building the right thing matters more than building things fast. Enterprises rarely arrive with a well-specified AI problem. They arrive with a vague ambition, a political landscape, and a lot of processes nobody has examined closely in years. Your job is to go in, work out where AI would actually change the economics of how they operate, say no to the tempting-but-worthless ideas, and then carry the good ones all the way through to something running in production.
You are not a salesperson who hands off to engineering, and you are not a project manager tracking someone else's plan. You own the why and the what; our Founding Engineer owns the how. The two of you are a pair, and you will spend a lot of time in the same rooms.
🚀 Key Responsibilities
Part One: Use-Case Diagnosis
Find the Real Problem: Embed with client teams to map how work actually happens, not how the org chart says it happens. Identify where AI would materially change cost, speed, or quality, and quantify it well enough that a CFO would accept the number.
Prioritize Ruthlessly: Most AI ideas inside a large enterprise are not worth building. Your value is as much in what you talk clients out of as in what you talk them into.
Write the Brief: Turn a diagnosed opportunity into a scoped problem statement our engineers can build against, including success criteria agreed with the client before work starts.
Part Two: Deployment Ownership
Own It End-to-End: Carry each engagement from first scoping conversation through pilot, production, and adoption. You are accountable for whether the thing actually gets used, not just whether it shipped.
Navigate the Organization: Align stakeholders from operations staff to C-suite. Large enterprises kill good projects through inertia and internal politics far more often than through technical failure, and steering around that is your responsibility.
Drive Adoption: A deployed system nobody uses is a failed engagement. Train users, redesign workflows around the tool where needed, and stay close enough after launch to know whether behavior actually changed.
Report Honestly: Keep both the client and the founding team accurately informed on progress, risk, and value delivered. No sugar-coating in either direction.
Part Three: Commercial Growth
Expand from Delivered Value: The most durable growth comes from having done good work. Turn successful deployments into the next engagement, the next business unit, the next contract.
Shape How We Sell: We are pre-revenue and have no playbook yet. You will help define what we sell, how we price it, and how we scope engagements so they are profitable rather than open-ended.
Support New Business: Sit in on new client conversations as the person who can speak credibly about what is genuinely feasible, which is often the difference between winning a deal and overpromising into one.
🎯 Candidate Profile & Experience Requirements
5 to 10 Years in a Problem-Diagnosis Role: Management consulting (strategy or technology), enterprise solutions consulting, chief of staff at a fast-growing company, or senior operational ownership in an industry you know deeply. What matters is a track record of walking into an unstructured situation and leaving with a defensible answer.
Exceptional Communication Skills: You can hold a room of skeptical executives, explain a technical trade-off without jargon, and tell a client something they do not want to hear while keeping the relationship intact. Fluency in both English and Vietnamese is required, and we weigh this as heavily as analytical ability.
Technically Literate, Not Necessarily Technical: You do not need to write production code. You do need to understand what current AI systems can and cannot do well enough to avoid promising things that are not real, and to earn the respect of the engineers you work alongside. If you have shipped something technical yourself, that is a plus.
Commercial Instinct: Comfortable talking about money. You can build a business case, defend a price, and recognize when a deal is shaped badly for us before we sign it.
Comfort with Ambiguity: We are pre-product. There is no methodology to inherit and no deck template waiting for you. You will build those.
Enterprise or Conglomerate Experience (Strong Plus): Prior work with large conglomerates, state-owned enterprises, or regulated industries in Vietnam or the region. Understanding how decisions really get made inside these organizations is worth a great deal here.
🎁 What We Offer
Our team and advisors come from McKinsey, Deloitte, Visa, the World Bank, and the Asian Development Bank, alongside engineers who have shipped at Meta, Google, Tesla, and TikTok. You'll be working with people who understand both how large institutions make decisions and what can actually be built.
We're deliberately small, and we're aiming for a very big impact, which means an outsized share of that impact will trace back to the handful of people in this room, you included. We operate on radical transparency and assume best intention in each other: no corporate politics, no bureaucracy, and a lot of trust placed in your judgment.
Realistic Scope to Shape the Company: You are not joining a go-to-market function. You are creating one, and the way you choose to run engagements will become how this company works.
Direct Access to Decision-Makers, Ours and Theirs: No layers between you and our founders, and you will regularly be in front of client executives rather than briefing someone else who is.
Ground-Floor Equity Upside: Meaningful equity in exchange for being one of the first people in the building, anchoring a high-profile technology launch with a leading private, multi-industry conglomerate in Vietnam.
High-Caliber Peers: Work closely with a small team of experienced operators and engineers, several coming directly from top Silicon Valley companies.
Top-of-Market Compensation: We pay at the top of market for this role: base salary, equity, and healthcare, structured for an early-stage team.
Thông tin chung
- Thu nhập: Thỏa thuận
Việc làm tương tự khác
Công ty Cổ phần Giải Pháp Nhân sự Việt Nam - HRchannels Group
Hà Nội, Bắc Giang, Bắc Ninh
Thỏa thuận
CÔNG TY CỔ PHẦN TƯ VẤN VÀ ĐẦU TƯ NAM SƠN
Hà Nội, Lạng Sơn, Thái Nguyên
45 - 60 triệu/tháng
CÔNG TY CỔ PHẦN XÂY DỰNG DÂN DỤNG CÔNG NGHIỆP HÀ NỘI
Hà Nội, Hà Nam
25000000-30000000 VND
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