AI applied Build & Delivery Lead
You don’t pitch with slides. You pitch with working demos. Work as one team with engineers and designers, bring prototypes that prove value and strategies that redefine the business — and drive transformation together from business design through delivery.
What you'll do
- Lead Business DesignStructuring client challenges and designing AI-native business models and strategies
- Demo to ConvinceWorking demos, not decks. Building prototypes as one team with engineers and designers that prove value in days
- Set Architectural DirectionDrawing system diagrams with engineers, evaluating trade-offs together, and shaping solution design
- Deliver as a TeamFrom prototype to production, driving hardening, scaling, and operations together with engineers and designers
- Work Across FrontsSimultaneous delivery quality across multiple accounts, balancing depth with breadth
- Champion Ethical AIFairness, privacy, compliance, and bias reduction practiced in every engagement
What we're looking for
Required Experience & Skills
Problem Framing
The ability to transform a client request like “increase revenue” into a structured question: “In which customer segment, at which touchpoint, and how should AI intervene to change the revenue structure?” Dig beneath surface-level requests to uncover structural challenges, define which problems to solve first, and draw out the essential questions that clients themselves have not yet articulated
Problem Solving
The ability to form hypotheses and move forward with minimal validation when the answer is unclear. Not “finding the right answer” but “making the most credible judgment within limited information and time.” Agility to learn quickly from failure, adjust direction, and keep moving forward
Communication
Discussing architecture with engineers, aligning UX direction with designers, explaining business impact to client executives — switching abstraction levels and language depending on the audience. Understanding each person’s position, concerns, and anxieties to build consensus and drive action
Business Design & Strategy
Structuring client business challenges and designing the impact AI can have on the business from revenue, cost, and operations perspectives. Not “we want to use AI” but “why should AI be applied to this specific process” — demonstrated with numbers and logic. Owning the full scope from investment decisions and roadmap design to risk assessment, informed by market structure and competitive landscape. Strategic consulting experience is a strong plus
Technology Literacy
Ability to discuss architecture with engineers as equals. Understanding technical trade-offs such as “Should we use RAG or fine-tuning?” and “Should we decompose into microservices?” and judging alignment with business requirements. Beyond foundational knowledge of algorithms, data structures, networking, and databases — being able to articulate why certain technologies were adopted and others became obsolete
Architecture & Development Methods
Understanding the strengths and constraints of major patterns such as distributed systems, event-driven, and microservices, and judging the right choice for each requirement together with engineers. Having practiced agile, waterfall, and other methodologies in the field — distinguishing “practices that are theoretically correct but actually slow delivery” from “practices that truly work”
Teamwork
Experience driving product delivery as one team with engineers and designers. Working with a “build together” stance rather than giving instructions, crossing role boundaries. Maintaining context and priorities across multiple projects while raising the team’s overall decision-making speed
ML/AI Fundamentals
Understanding of core machine learning concepts — supervised vs. unsupervised learning, model training and inference, neural networks, and transformer architecture fundamentals. Ability to evaluate AI solution feasibility, understand model limitations and biases, and make informed decisions about when ML approaches are appropriate vs. rule-based alternatives
Nice to Have
Data Platform
Understanding of cloud data warehouses such as Snowflake, Databricks, and BigQuery, and data pipeline configurations using dbt, Airflow, Kafka, and Spark. Ability to discuss AI product data foundations concretely with engineers
Cloud & Infrastructure
Knowledge of AI service deployment on AWS (Bedrock, SageMaker, Lambda), GCP (Vertex AI, Cloud Run), and Azure (Azure OpenAI). Understanding infrastructure automation concepts with Terraform, Docker, and Kubernetes, and ability to participate in cost and scalability decisions
Enterprise & BI
Understanding how enterprise systems such as SAP, Oracle, Salesforce, and ServiceNow are used in practice. Experience with data visualization and decision support using BI tools such as Tableau, Power BI, and Looker
Design & Experience
Understanding user research and experience design fundamentals, and ability to discuss with designers in a shared language. Reviewing prototypes in Figma, Sketch, and similar tools and providing feedback on experience direction
AI & LLM
Experience prototyping and designing products with LLMs such as OpenAI GPT-4 / o-series, Claude, and Gemini. Understanding of LangChain, LlamaIndex, AI Agents, and RAG concepts, and ability to incorporate them into client proposals
Interested in this role?
Tell us what drives you and what you want to build.