Artificial Intelligence Engineer

About OneByZero OneByZero is a Frontier Systems Integrator building agentic AI systems for leading banks, telcos, insurers, and retailers across Asia Pacific. We work on mission-critical problems for organizations operating the region's financial and digital infrastructure. Operating exclusively on AWS, we combine deep technical expertise with strong partnership programs that enable innovation, scale, and delivery excellence. We build with people who are technically serious, outcome-focused, and passionate about solving complex enterprise challenges. The Role The Forward Deployed Engineer (Agentic AI) builds production agentic systems inside regulated enterprises, on client infrastructure, with client data, under the constraints that banks, telcos, and insurers actually operate under. You are embedded in a client squad. You design, build, evaluate, and own production agentic systems end to end. You stay until the system works, the evaluations hold, and the client's team understands what they have. You leave behind something the next engineer can build on. At OBZ, you work alongside AI coworkers as your development partner. You direct them, review their output, validate it against your evaluation criteria, and use them to move faster than any individual engineer could alone. This is not a novelty. It is the model. This role is open to exceptional engineers with 4- 6 years of experience. What matters is not years of experience. It is the quality of your thinking, the depth of your curiosity, and the evidence that you have already been building with agentic tools because you wanted to, not because someone asked you to. What You Will Do Build production-grade agentic systems on AWS and OBZ's Neo platform: multi-agent orchestration, RAG pipelines, tool design, MCP server development, human-in-the-loop workflows, and the integration layer that connects agents to real enterprise systems with real data quality constraints and real security perimeters. Write evaluations before you write features. Define what good performance looks like, build the harness that measures it, and test against it throughout the build. In regulated environments, systems that have not been evaluated do not reach production. Integrate into enterprise reality. Legacy APIs, inconsistent data availability, access control constraints, and compliance requirements that were not designed for agentic systems. Build within those realities, not around them. Review and own what you build through production. Clean code, tested code, documented code. If the system degrades in production, you investigate. If the architecture needs to change, you contribute to the decision. You are accountable for what you ship. Practice DevSecOps from the first line of code. CI/CD, infrastructure as code, secrets management, IAM discipline, and observability are baseline practices. In regulated deployments, security is an architectural input from day one. Contribute reusable IP at every engagement: code modules, evaluation frameworks, deployment runbooks, agent design patterns. Every engagement leaves something the next squad can build on. Stay at the frontier. Know what AWS releases across its AI and agentic services stack. Know what the leading AI labs are publishing about production agentic systems: Anthropic, OpenAI, Google DeepMind, Meta, and the open-source frontier. Know what breaks in production and why. Bring that knowledge into your engagements before clients ask. Engage with client technical teams. Participate in design reviews, explain what you built when asked, and represent your work credibly in the room. Requirements What We Are Looking For Strong programming fundamentals in Python, with production-grade code discipline. Additional language experience in TypeScript, Java, or Go is a plus. Genuine agentic AI fluency. You have built with agent frameworks: LangGraph, LangChain, CrewAI, or equivalent. You understand RAG architectures, vector databases, prompt engineering at scale, evaluation harnesses, and the failure modes specific to agentic systems in production. At junior levels this can be demonstrated through personal projects and self-directed learning. At senior levels it must be demonstrated through production systems. AWS proficiency. You have built on AWS. You are working toward or hold AWS certifications relevant to your level, including AWS AI Practitioner, AWS Certified Machine Learning Engineer Associate, or AWS Solutions Architect. Anthropic certification is also valued. DevSecOps fluency. CI/CD, testing, infrastructure as code, and security hygiene are not optional. You know what a pull request review is for and you take it seriously. A strong academic foundation in computer science, engineering, mathematics, or physics. For recent graduates, this is the primary signal of aptitude we look for alongside evidence of self-directed building. Curiosity and ownership. You read what the labs publish. You experiment with what they release. You find the problem interesting. When something is broken you own the fix. Client-facing communication. You can explain what you built to a non-technical stakeholder with precision and without jargon. You participate in technical reviews with composure and represent your work credibly in the room. What Sets You Apart You have built a production agentic system that a regulated enterprise depends on, and you can walk through exactly what it does, how you evaluated it, where it failed in testing, and what you did about it. You have identified a production failure mode before it reached the client environment and fixed it under time pressure without anyone asking you to. You use AI coworkers to accelerate your engineering work and you have a clear point of view on which tasks they handle well and which ones still require your direct judgment. You have contributed a reusable technical asset that another squad adopted and you know which engagement is using it. What Success Looks Like The client has a production agentic system that is performing, that their team understands and can operate, and that is producing the outcome that justified the investment. OBZ has something reusable from every engagement you touch: a design pattern, an evaluation framework, a deployment runbook, a code module that the next squad picks up without starting from scratch. Your work compounds across the firm, not just within a single account. You are a more capable engineer at the end of every engagement than you were at the start. You have pushed into something you had not done before, solved a problem that was not in the playbook, and left evidence of that growth in the IP you contributed and in the engineers you developed alongside you. When all three of these are consistently true, you are succeeding at this role. Certifications AWS AI Practitioner, AWS Certified Machine Learning Engineer Associate, AWS Certified Solutions Architect (Associate or Professional), and Anthropic certification are all relevant and valued. Certification expectations are calibrated to level and assessed during the hiring process. Benefits What We Offer Competitive compensation benchmarked to market. The opportunity to work on AI transformation programmes that matter to the institutions millions of people in Asia Pacific depend on. A team that spans 10 markets, brings together some of the most experienced AI, data, and enterprise technology practitioners in the region, and moves fast without losing quality. Access to the AWS partnership programmes and frontier AI tooling that most firms in this region do not have. A firm that is building something genuinely new, with a leadership team that has scaled and delivered before. OneByZero is an equal opportunity employer. We are committed to building a diverse and inclusive team and welcome applications from candidates of all backgrounds. Why OneByZero Agentic AI in regulated enterprise is the hardest version of this problem. The clients are the institutions that run the financial infrastructure of Asia Pacific. The constraints are real. The stakes are high. OBZ is one of the few firms in the region doing this work at production scale in regulated industries, with an AWS partnership that puts you at the frontier of what is deployable. You will build systems that matter, work in squads small enough that your contribution is visible, and use AI coworkers as a genuine force multiplier. If you are at the start of your career and want to be shaped by the hardest agentic engineering problems in the region, this is where that happens. If you are experienced and want to work on problems that are still genuinely unsolved, this is also where that happens. Note - Only candidates with existing unrestricted work authorization in Singapore will be considered, as visa sponsorship is not available for this position