AI Engineer (Venture Discovery Pod)
About the company:
Altellect is a strategic venture ecosystem that builds, operates, and scales intelligent, high-growth startups across diverse sectors. As we expand our portfolio, we’re looking for passionate and driven professionals to join us in shaping the future of our ventures. We are on a mission to build and launch 10+ product-led businesses across multiple technology domains. At Altellect, you’ll help lay the foundations of innovation - from people and products to culture and performance - as we transform ideas into thriving businesses.
Role Objective:
Build rapid, end-to-end prototypes for AI-native ventures across sector-agnostic opportunities in the early product/venture discovery phase using modern AI and code/no/low-code tools to turn validated problems into working demos and technically feasible MVP scopes for studio investment committee review.
Who’s it for?
This role suits a hands-on, full-stack AI builder who is sector agnostic, enjoys jumping between wellness, health, travel, and other domains, and loves rapidly wiring together prototypes using tools like Cursor, Lovable, Supabase, n8n, and modern AI stacks.
Key responsibilities:
Build and iterate rapid prototypes and internal tools using AI-native workflows (e.g., Cursor, Lovable, Supabase, n8n, LLM APIs) to test venture concepts in 1–4-week sprints.
Implement end-to-end flows (backend, frontend, integrations) for 3–5 concurrent concepts across sectors such as wellness, health, travel, and other emerging spaces.
Design and run technical pilots and proof-of-concepts with real or simulated users to validate feasibility, performance, and cost.
Provide clear effort estimates, technical risk assessments, and recommendations that shape MVP scope and architecture.
Package and present demos, tech docs, and learnings to the CVA and AI PM to support go/kill and MVP decisions.
Domain expertise and experience:
Strong full-stack background (backend + frontend + integrations) with experience building web apps and APIs end-to-end.
Hands-on experience with AI and automation tooling: LLM APIs, vector databases, plus tools like Cursor, Lovable, Supabase, n8n, or equivalents.
Sector agnostic: comfortable diving into wellness, health, travel, and any new domain the studio pursues, with fast learning and curiosity rather than narrow specialization.
Must-Haves
4–6 years as a full stack engineer in startups or product companies, with a recent focus on AI-enabled products or automation.
Demonstrated track record of building and shipping quick-and-dirty prototypes using AI tools (Cursor, Lovable, or similar) plus backend/frontend code and services like Supabase and n8n.
Comfort working across multiple domains (wellness, health, travel, etc.) with a strong curiosity to learn new problem spaces quickly.
High ownership, bias for speed, and willingness to make pragmatic technical choices to validate quickly rather than over-engineering.
Good-to-Haves
Prior experience in a venture studio, startup lab, or innovation team where rapid prototyping was core to the role.
Familiarity with modern AI patterns (RAG, agents, workflow orchestration) and lightweight MLOps (deployment, monitoring).
Experience mentoring or collaborating closely with PMs and non-technical stakeholders to shape what to build next from a technical perspective.
Qualifications:
Bachelor’s in Computer Science, Engineering, or a closely related technical discipline.
Preferably a Master’s in AI/ML, Data Science, or related field, or equivalent experience with modern AI stacks (LLMs, RAG, agents).