Overview
AI Engineer – DX Orchestration & Intelligence Jobs in Jakarta Metropolitan Area at Tech Troops
Title: AI Engineer – DX Orchestration & Intelligence
Company: Tech Troops
Location: Jakarta Metropolitan Area
We are looking for an experienced AI Engineer – DX Orchestration & Intelligence to design, develop, and deploy AI-powered solutions that enhance Digital Experience (DX) operations within the MyTelkomsel ecosystem. This role focuses on building AI workflows, integrating Large Language Models (LLMs), Retrieval-Augmented Generation (RAG), and data-driven intelligence to automate business processes, generate actionable insights, and improve operational efficiency across multiple business domains.
Key Responsibilities
Design, develop, and maintain AI-powered applications and intelligent workflow automation solutions.
Build AI assistants using LLMs and Retrieval-Augmented Generation (RAG) with enterprise knowledge bases.
Develop AI-driven insight generators to automate executive summaries, operational reporting, business analytics, and dashboard insights.
Design AI recommendation engines that provide actionable business recommendations based on customer, transaction, campaign, product, and revenue data.
Develop AI solutions for reconciliation, settlement monitoring, discrepancy detection, anomaly detection, and root cause analysis.
Support campaign performance analysis, customer journey analytics, payment performance monitoring, and revenue trend analysis.
Develop AI capabilities for Quality Assurance (QA), including automated test case generation, defect classification, severity assessment, and testing support.
Integrate AI services with APIs, dashboards, data warehouses, Jira, spreadsheets, and internal enterprise systems.
Build scalable AI APIs and backend services for enterprise applications.
Ensure AI solutions comply with security, governance, data privacy, and internal compliance requirements.
Monitor AI model performance, evaluate response quality, and continuously improve accuracy, groundedness, and reliability.
Prepare technical documentation, API documentation, architecture designs, and user guides.
Required Qualifications
Bachelor’s degree in Computer Science, Information Technology, Artificial Intelligence, Data Science, or a related field.
2–5 years of experience in AI Engineering, Machine Learning, Data Engineering, or Backend Development.
Strong programming skills in Python and SQL.
Experience developing RESTful APIs using FastAPI or Flask.
Hands-on experience with Large Language Models (LLMs), Prompt Engineering, and Retrieval-Augmented Generation (RAG).
Experience with vector databases such as FAISS, Milvus, Qdrant, Pinecone, Weaviate, or pgvector.
Knowledge of machine learning fundamentals, model evaluation, and AI workflow development.
Experience working with Docker, Git, cloud deployment, and CI/CD practices.
Strong data processing skills using Pandas, Polars, or PySpark.
Experience integrating AI solutions with enterprise systems and APIs.
Preferred Qualifications
Experience with OpenAI, Azure OpenAI, Google Gemini, Anthropic Claude, or other enterprise LLM platforms.
Familiarity with LangChain, LlamaIndex, and AI orchestration frameworks.
Experience with PostgreSQL, MySQL, Redis, Elasticsearch/OpenSearch, Airflow, BigQuery, or other data platforms.
Understanding of payment systems, reconciliation, settlement processes, customer journey analytics, campaign management, and digital business operations.
Knowledge of AI governance, monitoring, prompt versioning, and LLMOps practices.
Excellent analytical, problem-solving, and communication skills.
Ability to translate business requirements into scalable AI solutions.
Key Deliverables
AI-powered APIs and enterprise AI services
RAG-based Knowledge Assistant
AI Insight Generation Platform
AI Recommendation Engine
AI Defect Classification Solution
AI Reconciliation & Settlement Assistant
AI Campaign Analysis Workflow
Prompt Library and Version Control
AI Monitoring Dashboard
Technical and API Documentation
Architecture Design and User Documentation
Success Metrics
Reduced manual reporting and operational effort
Faster reconciliation and settlement analysis
Improved campaign performance insights
Reduced defect classification and test case preparation time
High AI response accuracy and groundedness
Low hallucination rate
Increased AI adoption across DX teams
Scalable, secure, and production-ready AI solutions
Improved operational efficiency and business decision-making
