AI and Data Specialist
Indexed description
In our 10+ years of journey we have reached over 3 Million platform users, and we're not planning to stop any time soon. We need more people like you: builders and owners with calculated ambition who are ready to #ElevateThroughImpact and raise Indonesia's software standard.
Job Description:
The AI/Data Builder is an AI-native Builder who owns AI, ML, LLM, data, and non-deterministic system quality. This role expects to stay close to users and ships end-to-end, user-accessible AI/data products, features, modules, workflows, services, and decision-support capabilities. What sets this role apart is deeper accountability for the quality of probabilistic behavior, data quality, model behavior, evaluation systems, AI trust, guardrails, and continuous improvement. The mission: build, ship, measure, and improve AI/data capabilities that are useful, safe, trusted, measurable, and valuable for users.
- User & product alignment. Stay close to workflows, feedback, and production behavior to define what "good vs. unacceptable" AI behavior looks like for the use case.
- Build & ship. Develop AI services, ML models, LLM workflows, RAG systems, data pipelines, and model integrations as real product capabilities (not just experiments).
- Configure & construct. Own prompts, retrieval logic, model configs, orchestration flows, and data transformations.
- Validate quality. Test behavior through eval sets, golden datasets, scenario/adversarial tests, regression evals, and human review.
- Manage risk. Handle grounding, hallucination, bias, privacy, latency, cost, and drift concerns.
- Release responsibly. Ship with guardrails, fallbacks, monitoring, and human-in-the-loop controls.
- Iterate. Continuously improve prompts, models, and pipelines based on real usage data.
- Cross-functional collaboration. Partner with Platform Builders (deployment, agent tuning) and Product Builders (user value, trust boundaries, release readiness).
- 2 - 3+ years in full-stack engineering or applied software development using AI/data use cases.
- Experience with AI, ML, LLM, RAG, data, analytics, and intelligent product systems.
- Proficiency in prompt, context, retrieval, model, orchestration, and data-system design.
- Experience with data pipelines, data quality, freshness, lineage, completeness, and correctness.
- Demonstrated ability with evaluation design, golden datasets, regression evals, scenario tests, and human review.
- Working knowledge of grounding, hallucination control, refusal behavior, guardrails, safety, and trust.
- Experience monitoring for drift, quality degradation, latency, cost, user feedback, and production behavior.
- Track record shipping AI/data-powered products, features, modules, workflows, services, or decision-support capabilities.
- Preferred Traits
- Experience collaborating with Platform Builders on agentic build workflows, especially agent tuning, evaluation, and improvement.
- Comfort defining risk tolerances and behavior standards for non-deterministic systems (i.e., systems where output varies based on models, prompts, retrieval, data, context, or user input, and can't be verified by exact-output tests alone).
- Mindset
- A builder who takes deep ownership of AI/data behavior quality — someone who treats evaluation, monitoring, and continuous improvement as core parts of shipping, not afterthoughts, and who partners naturally with Product and Platform counterparts (this role isn't research-only, model-only, or analytics-only — it's about shipping real AI/data-powered capability and managing its quality in production).
Don't forget to check our Recruitment FAQ at bit.ly/FAQMekariHiringENG or bit.ly/FAQMekariHiringINA to find the answers to commonly asked questions regarding our recruitment process.
We wish you the best. Hope to see you around soon!
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