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Portcast is a venture-backed, Singapore-based logistics technology startup building a real-time transportation visibility platform for global supply chains. We help shippers, manufacturers, and logistics service providers turn data into decisions and decisions into measurable business impact. Our platform goes beyond visibility. Portcast enables action at scale by surfacing the right risks early, helping teams prevent detention and demurrage, accelerate exception management, and close invoices faster with built-in evidence. We turn visibility into outcomes: reduced costs, improved operational control, and more predictable supply chains. Founded in 2018 and backed by leading technology investors, we are building for an industry at a critical inflection point of digital transformation. Our team of software engineers, data scientists, and logistics experts is on a mission to make supply chains not just visible, but decisively actionable end-to-end. ABOUT THE ROLE: We're looking for our Head of Tech (Engineering, AI, Data) to lead, own, and shape our technical direction. This role will own and lead our 15-person Tech team, which is made up of 3 functions: Engineering, ML/DS, and DA. You'll be responsible for how we build, how we use data and AI, and how our systems scale as the company grows. We're looking for a strategic technical leader who thinks from first principles, makes strong decisions, and stays close to the technology. Someone who has shipped enterprise-grade software: products with real SLAs, multi-tenant boundaries, security reviews, and the procurement-and-pilots dance that comes with Fortune-500-class customers. Someone with a strong, defensible point of view on where AI belongs in production vs. where it's still a science project. And critically: someone who came from the code, still writes it when it matters, and would rather review an RFC than sit through another roadmap slide. You'll work closely with the CEO, Product, Sales, and CS teams to translate real customer problems into systems, tools, and AI capabilities that drive outcomes, value to our customers and company revenue, not just features. This is not a pure management role. It requires strong technical judgment, comfort operating across engineering and data, and the ability to lead through both direction and execution. You'll set the technical bar, strengthen how teams work together, and ensure engineering, ML, and analytics move as one cohesive capability supporting the business. WHAT SUCCESS LOOKS LIKE IN THIS ROLE: Software Engineering, ML, and Analytics operate as a clear, structured, and high-performing unit with defined ownership and strong delivery predictability.Technical decisions are grounded in first-principles thinking, scalable architecture, and long-term product clarity.AI and data capabilities are consistently deployed into production and directly tied to measurable business impact. WHAT YOULL OWN: Engineering Leadership & Architecture Own technical direction across platform, infrastructure, and product systemsDefine scalable architecture and ensure reliability, performance, and securityImprove engineering velocity, code quality, and delivery disciplineStrengthen documentation, ownership, and system clarityMentor tech team: Engineering, ML, AnalyticsAI, Data Science & Analytics Strategy Define how AI and data drive competitive advantage in our productEnsure ML models move from experimentation into production environmentsStrengthen MLOps, data pipelines, and real-time data systemsAlign analytics insights with product and customer decision-makingEnsure AI investments translate into real outcomes, not just experimentsProduct & Business Alignment Partner closely with Product to shape technical roadmapWork with Sales and Customer teams to understand enterprise requirementsGuide solution design for complex customer use casesEnsure engineering effort maps directly to business impactTeam, Culture & Organizational Development Lead and develop Engineering, ML/Data Science, and Analytics teamsHire strong senior talent and raise the technical barCreate clarity in roles, responsibilities, and technical ownershipReduce single-point dependency across critical systemsBuild a culture of accountability, curiosity, and effectivenessHands-On Technical Leadership Stay close to architecture and key system decisionsReview critical designs and technical proposalsStep into complex technical problems when neededPrototype or validate high-impact ideasLead by example in technical depth and problem solving WHAT WERE LOOKING FOR: 10+ years in software engineering, data, or ML environmentsBachelors, Masters, or PhD in Computer Science, Engineering, or a related fieldSoftware heavy background who understands data, AI, system design and infrastructureExperience leading technical teams in a startup or product-driven B2B SaaS companyTrack record building and scaling production AI/ML systemsExperience with distributed .
Here's how to pick the right one and stand out in your application.
144.883Jobs
31.687IN
81%EN
That number is real. WorkMundi's database shows 144,883 open engineer roles across the world. India has the most with 31,687 jobs, followed by the United States with 30,084. If you just finished reading one job ad and felt paralyzed by choice, you're not alone—but this scale is actually an advantage. It means you can afford to be selective.
Start by geography and language. The majority of engineer ads—117,837 of them—have the job posting text written in English. Use that as one filter, but remember: the ad text language tells you nothing about whether the role actually requires you to speak English day-to-day. Read the job description carefully. Then check which countries have the volume you're targeting. Singapore, Poland, and Australia round out the top five after India and the US.
Next, learn who's hiring. Accenture has posted 2,801 engineer roles. andurilindustries, speechify, and jobgether are also actively recruiting. If you're applying to one of these names, research their hiring patterns and interview style before you apply. That homework pays off.
When you interview, expect the question every engineer hears: 'Tell me about a time you had to debug a problem that wasn't in your job description.' Have a specific story ready—not a general one. Name the tools, the deadline pressure, and what you learned. Hiring managers listen for whether you see problem-solving as part of the role itself, not a favour.