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J&F in Bengaluru is hiring a Technical Product Manager to own delivery across 15–25 engineers across backend, frontend, and AI, turning structural and detailing engineer requirements into scoped software.
This is a technical role where you shape plans, manage dependencies, and push for scalable, deterministic automation. You collaborate with CAD/PLM domain experts and ensure releases are truly done.
We are hiring one Technical Product Manager to own delivery across our engineering teams in Bengaluru. You will run 15–25 engineers across backend, frontend, and AI workstreams, and you will be the person who turns requirements originating with our structural and detailing engineers into scoped, sequenced, shipped software.
This is a technical role. You will not be handed a groomed backlog and asked to move cards across it. You will sit in the design discussion and have a view on how and when — you will push back on an approach that will not scale, ask why a trade‑off was made, and know the difference between a two‑day change and a two‑sprint one. You are not expected to write production code. You are expected to read it, understand the system, and never be the least‑informed person in a technical conversation you are chairing.
Our requirements do not come from a product spec written in a vacuum. They come from structural and detailing engineers sitting on the floor with decades of practice behind them. Converting that into software is the defining skill of this job.
We prefer to be candid. These are the problems that make this role genuinely difficult — and genuinely interesting.
Our structural and detailing engineers know what a correct drawing looks like, but much of that knowledge is tacit. Your job is to extract it into deterministic, testable rules before an engineer starts building. Getting this wrong is the single most expensive failure mode we have — it produces work that looks finished and is not.
Backend (AWS serverless), frontend (Angular / React), and AI engineers ship into the same product. They have different failure modes, different testing regimes, and different natural cadences. Sequencing them so nobody idles and nothing integrates late is the core scheduling problem here.
This is construction software. A wrong drawing, a wrong quantity, a wrong permission, or a wrong payroll figure has consequences outside the screen. “Ship it and iterate” has limits here, and you will need judgement about exactly where those limits sit for each workstream.
Drawing generation and extraction work is research-shaped: some weeks produce a breakthrough, some produce a negative result. You will plan around that uncertainty honestly— with timeboxes, decision points, and fallbacks — instead of pretending an unknown is a two‑week ticket.
Companies run their operations on this platform daily. Production incidents, customer escalations, and enterprise integrations (Asite, Autodesk Construction Cloud) compete with roadmap work for exactly the same people. You will make that trade‑off explicitly, every week, and be able to defend it.
The operations platform and the drawing‑automation platform have different customers, different rhythms, and partly shared people. Keeping both moving — without either becoming the perpetual second priority — is a standing constraint on every plan you make.
Direction can change on new customer information, and sometimes it should. You are the shock absorber: re‑plan quickly, communicate the change clearly and once, and make sure the team experiences it as a decision rather than as chaos.
Engineers respect the questions you ask, not just the dates you set.
Measures the job by what shipped and worked, not by how busy the board looked.
Says the uncomfortable thing early, in plain language, to the person who needs to hear it.
Leaves every process, plan, and hand‑off simpler than they found it.
Strong views on how to run delivery, updated when the evidence changes.
The team becomes more predictable and more capable because you are in it.
Skills:- AutoCAD, Product Lifecycle Management (PLM), EDA, Agile/Scrum, CI/CD, NodeJS (Node.js), Artificial Intelligence (AI), Machine Learning (ML) and Data Science