Three routes and five profiles. These are conversations about building the founding team and expressions of interest for forthcoming internships, not five salaried vacancies, fixed appointments or a promise to fill every profile. Each profile has its own email subject; each button opens your email application. Before writing, see how your message is handled.
Founding team
We are assembling the founding team across product engineering, industrial expertise and commercial development. The scope, commitment, working arrangements and start date will be agreed individually before collaboration begins.
Product engineering (Python / full stack)
Turn the tested calculations and review records into a product that people outside the team can rely on: structured inputs, source-linked records, corrections that keep their history, interfaces, tests and controlled deployment.
Subject: Axiocost — Founding Product Engineer · Full description
Write about product engineering ↗
Industrial and cost-engineering expertise
Bring practice from cost engineering, should-cost analysis, industrial procurement or operations: decide what a credible review must contain, test the method against how industrial decisions are really made, and shape how pilots are scoped.
Subject: Axiocost — Founding Industrial Lead · Full description
Write about industrial expertise ↗
Commercial development and industrial B2B partnerships
Find the organisations for which Axiocost addresses a real problem, shape pilot proposals that are honest about scope and evidence, and build partnerships with industrial companies.
Subject: Axiocost — Founding Commercial Lead · Full description
Write about commercial development ↗
Technical internship
We are inviting interest for a forthcoming supervised internship. The project, duration, dates, working arrangements and applicable placement agreement will be agreed before the start, taking account of the learning objectives and the candidate’s availability.
A supervised, bounded product-engineering contribution: for example, strengthening the tests around a calculation, making a fictional example explain its assumptions more clearly, or adding a validation check to a review record.
Subject: Axiocost — Technical Internship · Full description
Write about the technical internship ↗
Functional internship
We are inviting interest for a forthcoming supervised internship. The project, duration, dates, working arrangements and applicable placement agreement will be agreed before the start, taking account of the learning objectives and the candidate’s availability.
A practical product, workflow or industrial-expertise assignment; coding is not required. For example: exploring how buyers, engineers and finance would use the tools, building a small prototype or review aid, writing fictional cases, observing usability, and turning what you see into actionable requirements.
Subject: Axiocost — Functional Internship · Full description
Write about the functional internship ↗
Both internships have a defined learning objective, a designated supervisor and a bounded contribution. Initial work uses fictional data. Contributions may be incorporated after review; interns do not independently own production systems, security decisions or real industrial approvals.
A short introduction, your availability and a link to work you are free to share are enough for an initial conversation. A CV, public profile or portfolio is welcome but optional; no cover letter or new deliverable is required at this stage.
Applying does not require any contribution to the public repository. Please do not send confidential drawings, supplier cost breakdowns, customer files or lists, contracts, employer code or proprietary templates, nor identity documents or health information.
What happens next: Philippe Dagher reviews each message personally. Where there may be a fit, the next step is an initial conversation about relevant work you have already completed or experience you can share, and a mutual clarification of the proposed role. No test or new deliverable is requested before that conversation.
Backgrounds are examples, not cumulative requirements.
Founding team · Product engineering (Python / full stack)
The calculations work. Now make the product work for someone who did not build it.
The role. Own a coherent review experience rather than a collection of disconnected features, and help shape the architecture and product priorities rather than implement a fixed specification. The starting point is the private Python prototype, its automated tests, the public method packs and the fictional examples, not a blank repository.
What you would work on. Clear interfaces for structured inputs, comparisons, source-linked evidence, missing information and recorded corrections; connecting them to the tested calculation and workflow components without losing assumptions, units, revision history or the difference between a recommendation and an executed action; appropriately scoped persistence, APIs and review records; reproducible setup, tests and deployment; and assisted document interpretation where it solves a real problem, deciding what should be deterministic, what could be AI-assisted and what must remain a human decision.
A useful first outcome. One complete review on fictional data: load a case, understand its assumptions, make a supported correction, see what changed and identify the evidence still missing, done by another practitioner without the developer narrating every screen.
Backgrounds we welcome. Python and web-application development, sound software-engineering judgement and an interest in product design; JavaScript or TypeScript, structured data, version control and automated tests. Having shipped something other people use matters more than any particular framework. Industrial knowledge is welcome; curiosity about the domain is essential.
Where to start. The interactive quote comparison, the value-delivery recording and the public method packs.
Founding team · Industrial and cost-engineering expertise
A mathematically correct estimate can still lead to the wrong industrial decision.
The role. Turn industrial experience into explicit questions, evidence requirements and reviewable decisions: help choose where the product should begin, challenge what the model assumes, and decide which questions the tool can support and which need an expert. This is hands-on work building the venture, not an honorary advisory position.
What you would work on. A narrow set of valuable cost or purchasing decisions and the technical, commercial and operational information needed to assess them; process routes, material and quantity assumptions, capacity, setup allocation, logistics and quotation boundaries, without presenting one costing convention as universal; fictional reference cases that expose differences, omissions and trade-offs; manufacturing judgement translated into requirements for product engineering; and the link from an opportunity to qualification work, responsibilities, capacity, dates and evidence of outcomes. The current Cost Engineering pilot hypothesis is non-safety-critical molded components, a scope the right specialist can help refine.
A useful first outcome. One bounded industrial review case: the decision to make, the evidence required, the assumptions worth testing, the options to compare and the conditions that change the conclusion. Success is an expert recognising both the usefulness and the limits of the analysis, not an impressive but unsupported savings figure.
Backgrounds we welcome. Should-cost analysis, value engineering, manufacturing engineering, supplier development, technical procurement or industrial performance; industrialisation, quality qualification, sourcing or benefit verification. Depth in one domain matters more than a claim to know every process. Coding is not required.
Where to start. The Cost Engineering offer, the public Cost & Value Engineering method and the value-delivery recording.
Founding team · Commercial development and industrial B2B partnerships
An impressive demonstration is not the same thing as a problem someone will pay to solve.
The role. Lead disciplined customer discovery and develop credible pilot relationships: help the technical and industrial team understand who has the problem, how it is handled today, who decides and what improvement would justify a continued relationship. You would shape the offer itself as well as how it reaches the market.
What you would work on. Conversations with purchasing, manufacturing, operations and finance that tell buying intent apart from general enthusiasm; the choice of a first customer segment and use case; pilot discussions with a named sponsor, a bounded scope, a legitimate route for sharing information and an agreed way to assess usefulness; positioning and proposals that claim nothing the product has not established; a small, well-qualified pipeline whose objections feed back into product decisions; and practical partnerships, without implying endorsements or agreements before they exist.
A useful first outcome. A small set of well-understood pilot opportunities, each with its problem owner, current process, review effort, available evidence and a definition of a useful result. A large contact list is not the objective.
Backgrounds we welcome. Industrial B2B software, engineering services, procurement technology, operational-improvement solutions or similarly consultative markets; working with engineers and defining pilot scope. A relevant network helps, but this is not a request to hand over contacts. French and English are both relevant to the conversations we intend to have.
Where to start. The two offers, Cost Engineering and Value Delivery, and how each pilot is framed.
Technical internship
Build something another person can understand, test and use, not just a demo that works on your laptop.
The work. One bounded, supervised contribution to the review experience, agreed with your supervisor and, where relevant, your educational institution. Examples: explaining a fictional example’s assumptions, missing information and outputs before changing it; helping build a structured-input view, evidence panel or before-and-after comparison; writing and extending automated tests or investigating a reproducible defect; improving setup instructions so someone else can run the example from a clean checkout; documenting the contribution and presenting a short demonstration.
A useful first outcome. A small usable feature or reliability improvement, with its tests and a clear handover: for example, a fictional quantity correction becomes visible in the interface, the resulting change is explained, and missing information stays explicitly unknown.
Backgrounds we welcome. Software engineering, computing, data, applied mathematics or engineering; some Python and basic web development. A university exercise or personal project is enough to start a conversation, and no prior knowledge of industrial costing is expected. AI coding assistants may be used through approved tools; understanding their output is part of the learning.
Where to start. The interactive quote comparison, the value-delivery recording, and the reference code and tests in the public method packs.
Functional internship
A product can pass every software test and still confuse the person who needs it.
The work. A practical assignment on the product, a workflow or an area of industrial expertise; coding is not required. Map one user’s task: the decision to make, the information needed, the uncertainties and the expected output. Work through fictional examples to find confusing wording, missing explanations or unnecessary steps; build a simple mock-up, form, no-code prototype or structured review aid with an approved tool; test the journey with authorised participants, under supervision; and turn what you observe into prioritised requirements and acceptance criteria. The assignment produces something usable; it is not an open-ended literature review.
A useful first outcome. One tested user journey, a small demonstrable prototype or review aid, and a prioritised findings note: for example, helping a reviewer tell an expected annual gain from a first-year scenario and an unmeasured outcome, without the developer translating every label.
Backgrounds we welcome. Industrial engineering, procurement, supply chain, operations, finance, business analysis, product management or service design. Structured thinking, careful writing and useful questions matter more than a programming language or a prestigious course.
Where to start. The value-delivery recording, the interactive quote comparison and the public Value Delivery method.