Indonesia's first and fastest-growing on-demand platform for groceries and essentials.
Anything you need, fast.
Astro is Indonesia's first quick commerce company that delivers groceries and essentials to your door within 15 minutes. 24 hours a day, 7 days a week.
Just like real Astronauts that take off into outer space, Astro embodies the values of being fast, bold, adventurous, and technologically advanced. Download our app now to experience and enjoy the new definition of fast!
Interested in working for a company that pushes the boundaries and strives to be the best? Join us now to be a part of this ground-breaking mission!
About this Position
As a Senior Forward Deployed Engineer, you will own AIRO engineering delivery end-to-end; designing, building, releasing, and operating customer-facing AI capabilities across product discovery, supported cart and payment journeys, platform assistance, and post-purchase support. You will work directly with business users and external stakeholders to observe workflows, discover root-cause bottlenecks, and define clear value and success metrics before writing code. Balancing technical practicality with business impact, you will architect, test, and deploy production software: integrating APIs, data flows, shared AI capabilities (retrieval, tool use, and agent workflows), and intuitive user interfaces. Beyond deployment, you will evaluate conversational reliability, monitor latency and AI quality in production, and co-design with users to drive adoption and continuous improvement.
Job Description
As our Astronaut, your missions are:
- Own AI project engineering delivery. Design, build, release, and operate customer-facing AI capabilities across product discovery, supported cart and payment journeys, platform assistance, and post-purchase support, in partnership with the relevant service owners.
- Discover and validate problems. Understand customer journeys through feedback, usage data, and execution traces; embed with business users to observe workflows and investigate bottlenecks, errors, repetitive tasks, and knowledge gaps.
- Define value before building. Establish baselines, identify accountable stakeholders, prioritize opportunities, and agree on success measures, acceptance criteria, and experiment stop conditions.
- Choose practical solutions. Compare process changes, existing tools, system integrations, custom software, data solutions, and AI against expected value, delivery effort, operating cost, and risk.
- Build and deliver end to end. Write, review, test, and deploy production software across APIs, integrations, data flows, automation, and user interfaces as needed. Iterate through small releases and direct user feedback.
- Apply AI to real workflows. Integrate approved models and shared AI capabilities; implement retrieval, tool use, structured outputs, and agent workflows where justified by the problem.
- Evaluate quality and reliability. Define representative customer-journey and workflow evaluations, investigate failure modes, and implement appropriate access controls, confirmation, human escalation, fallback, and recovery behavior. Validate conversation context, factual grounding, and the correctness of actions across retries and partial failures.
- Drive adoption and improve experience. Work with Product and Design on customer usability and task completion. For internal workflows, co-design with users, demonstrate progress, train users, and address adoption barriers.
- Own production operation. Coordinate releases, monitor reliability, latency, AI quality, and cost, troubleshoot incidents, and continuously improve AIRO and assigned solutions. Establish ongoing ownership explicitly and transfer support only through an accepted handover.
- Prove business impact. Compare results with the agreed baseline and recommend whether to scale, improve, transfer, or stop an initiative.
- Make learning reusable. Document decisions, runbooks, integrations, and delivery patterns; share platform needs and reusable improvements with the relevant engineering owners.
Job Requirements
In order to launch the missions successfully, you need to have:
- 5+ years of experience in Backend Engineering or Software Engineering, with demonstrated senior-level ownership of production-grade systems. Prior experience in an FDE role is not required.
- Strong understanding of RESTful APIs, microservices, databases, distributed systems, and system design, including experience designing and developing scalable, highly available backend services.
- Solid understanding of software engineering principles, clean code, testing, version control, and CI/CD practices.
- Experience working with cloud infrastructure and modern engineering tools and processes.
- Strong debugging and problem-solving skills in production environments, including monitoring, incident resolution, and continuous improvement of performance and reliability.
- Demonstrated ability to independently own a product capability or solution from problem discovery and technical design through implementation, deployment, and ongoing production improvement.
- Hands‑on experience building and evaluating LLM-powered applications or workflows, with an understanding of model limitations, failure handling, and quality, latency, and cost trade-offs. No fixed number of years in AI or FDE roles is required.
- Ability to translate customer needs into reliable product experiences and assess usability, task completion, correctness, and performance, supporting ownership of AIRO, Astro’s customer-facing AI.
- Ability to work directly with business users, identify root causes, clarify ambiguous requirements, and choose practical solutions across process improvement, software, data, and AI.
- Strong cross‑functional communication with Product, QA, Frontend, Data, and business stakeholders, including the ability to explain technical trade-offs, constructively challenge assumptions, and align priorities and scope.
- Ability to work effectively in a fast-paced environment with evolving requirements and tight delivery timelines, prioritizing work and making sound trade-offs between speed, quality, and scope.
- Ability to define success criteria and use data and feedback to evaluate customer outcomes, adoption, and business impact.
- Sound judgment about security, access permissions, sensitive data, and the consequences of automated actions.