{"id":3613170,"url":"https://alion.io/job/hivve-sg-ai-prompt-engineer","title":"AI Prompt Engineer","company":{"id":4494819,"name":"Hivve Sg","domain":"hivveimpact.com","url":"https://alion.io/company/hivve-sg","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":null,"truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":null,"employment_type":"part_time","work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"posting_text","remote_working_hours":null,"hiring_geo_confidence":"explicit","locations":["Singapore"],"countries":["SG"],"hiring_countries":["SG"],"hiring_countries_total":1,"salary":{"min":900,"max":1200,"currency":"SGD","period":"month","gross":true,"usd_annual":11268},"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"AWS","optional":false},{"name":"Function Calling","optional":false},{"name":"GitHub","optional":false},{"name":"Hallucination","optional":false},{"name":"Prompt Engineering","optional":false},{"name":"Python","optional":false}],"status":"live","first_seen_at":"2026-11-02T00:00:00Z","employer_posted_date":null,"last_verified_at":"2026-11-02T00:00:00Z","board_verified":false,"closed_at":null,"days_open":4,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":4},"description":"Role Type: Part-Time\nTime Commitment: Min of 20 hours per week - Full time (optional)\nAttendance: Weekly team meetings; Quarterly Townhalls; Availability for scheduled meetings during agreed working hours\nWorking Schedule: Monday -Friday\nDuration: 3 - 6 months \nReporting to: CEO, Solution Architect \nStart date: Early November 2026\nLocation: Central Singapore (Hybrid – flexible combination of in-person and remote work)\nTools: Python, GitHub, AWS, LLMs \nPerks & Allowances: $900 SDG monthly\nOverview\nHivve is a global impact reporting company working with universities, foundations, and purpose-led organisations across eight countries. We are on a mission to transform how organisations capture and communicate their impact, using AI tools and our proprietary data models to make impact reporting simpler, smarter, and more meaningful.\nAbout the RoleThis is a hands-on AI Prompt Engineer Internship for a minimum 3 months, with the option to extend. You will work at the intersection of product, engineering, and applied AI, helping to design, test, and refine how large language models are used within a SaaS platform. The role begins with structured prompt development and evaluation in controlled environments, and may extend into direct exposure to live production systems where AI outputs are actively used by real users. You will gain experience across the full lifecycle of AI systems—from early experimentation through to production monitoring—while working closely with engineers, product teams, and domain experts.Key ResponsibilitiesTranslate user, client, and internal requirements into structured prompts and clearly defined output specifications\n\nDesign, test, and iterate prompts to improve accuracy, consistency, and usability across core workflows\n\nSupport Alpha and Beta testing phases through structured experimentation and systematic identification of failure modes\n\nEvaluate AI outputs using defined criteria including accuracy, reliability, edge cases, and hallucination risk\n\nCollect, synthesise, and apply feedback from users and stakeholders to improve prompt and model performance\n\nTest prompts across staging and production-like environments, and (in extension phase) monitor performance in live production systems\n\nWork with multiple concurrent AI outputs and use cases, ensuring consistency and quality across different workflows\n\nContribute to the development of evaluation frameworks, monitoring approaches, and quality benchmarks for production systems\n\nAssist in the development and refinement of AI agent workflows, including prompt chaining, tool use, and orchestration\n\nCollaborate with engineers and product teams to understand system constraints, production behaviour, and deployment requirements\n\nDocument prompt iterations, production learnings, and best practices to support scalability and knowledge sharing.\n\nSupervision and Support\nWeekly in person check-ins with the CEO and senior development team with virtual collaboration with the Architect. \n\nClear task briefs and achievable milestones each week.\n\nExposure to international projects at the intersection of AI and social impact.\n\nWho We’re Looking ForStudents or recent graduates in Computer Science, Artificial Intelligence, Data Science, or a related technical field\n\nStrong interest in AI, large language models, and how generative AI is applied in real-world SaaS products\n\nFamiliarity with Python, basic database concepts, and core AI/ML principles (e.g. training data, evaluation, model behaviour)\n\nStrong analytical and problem-solving skills, with the ability to structure ambiguous problems into testable approaches\n\nCuriosity and experimentation mindset, particularly in understanding how prompts influence model outputs and system behaviour\n\nInterest in applying AI for social and environmental impact, and building technology that delivers measurable value\n\nComfortable working in cross-functional teams, including product, engineering, and domain experts\n\nClear written communication skills, particularly in documenting experiments, outputs, and insights\n\nA self-starter who is proactive, enjoys learning quickly, and can operate independently in a fast-moving environment\n\nWillingness to work flexibly, including later afternoon or evening hours where needed, to coordinate across global time zones\n\nComfort working in fast-moving environments where you may be supporting multiple live AI outputs and use cases simultaneously during the extension phase\n\nSkills\nLiaising with cross functional teams, Database Implementation, Production Testing, Requirement Specification, Experimentation, Failure Modes, Quality and Performance, Measuring Technology, Model Checking, Computer Science, Generative AI Application Development and Deployment in Financial Services, AI Evaluation, Structural Testing, Engaging Stakeholders, Generative AI Prompt Engineering, Concurrent Programming, integrated 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