About the Company
Techtanium is a fast-growing technology consulting and solutions company operating across Asia and international markets. We specialize in high-stakes digital banking transformations. In an era of rapid technological change, we are committed to being an AI-First organization, leveraging cutting-edge intelligence to redefine how software is built, tested, and delivered.
About the Role
We are looking for a forward-thinking AI Enablement Engineer to revolutionize our Software Development Life Cycle (SDLC). Your mission is to integrate Artificial Intelligence into our engineering workflows, reducing manual toil and accelerating the delivery of our digital banking products. You will build internal AI tools, optimize developer environments with AI assistants, and establish AI-first engineering standards. This role requires a unique blend of backend engineering excellence and a deep understanding of LLM orchestration. As we operate extensively across Asia, professional-level fluency in both Chinese and English is a mandatory requirement for this role.
Responsibilities
- AI Tooling & Integration: Evaluate, deploy, and customize AI-assisted coding tools (e.g., GitHub Copilot, Cursor, Tabnine) across our regional engineering hubs.
- Workflow Automation: Identify bottlenecks in the delivery processfrom requirements gathering to deploymentand design AI-driven solutions to automate them.
- Internal RAG Systems: Build and maintain internal Retrieval-Augmented Generation (RAG) systems to help developers and analysts navigate complex banking specifications, compliance documents, and legacy codebases.
- AI-Assisted QA: Collaborate with the QA team to implement AI-driven test case generation, automated bug triaging, and synthetic data generation.
- Prompt Engineering & Training: Act as the internal subject matter expert; conduct workshops in both English and Chinese to upskill developers on using LLMs effectively and safely.
- Governance & Security: Establish guidelines for the secure use of AI, ensuring proprietary banking logic and sensitive client data are protected according to international security standards.
Qualifications
- Bachelor's degree in Computer Science, Artificial Intelligence, or a related field.
- Proven track record of improving team productivity through automation or custom tool development.
Skills Required
- AI & LLM Expertise: 2+ years of software engineering experience with a strong focus on LLM integration. Proficiency in using and fine-tuning LLM APIs (OpenAI, Anthropic, Google Gemini, or open-source models like Llama/Mistral). Hands-on experience with AI frameworks such as LangChain, LlamaIndex, or Haystack. Deep understanding of Vector Databases (e.g., Pinecone, Milvus, Weaviate) and embedding strategies.
- Core Engineering: Strong proficiency in Python (primary for AI tooling) and Java/Spring Boot (to interface with our core banking stack). Experience with CI/CD pipelines (GitLab CI, GitHub Actions) and injecting AI-driven automated checks. Familiarity with Modern DevOps (Docker, Kubernetes) to deploy internal AI microservices.
- Data & Architecture: Knowledge of data processing and ETLessential for preparing clean data for AI training or RAG indexing. Solid understanding of API design and microservices architecture.
Skills Preferred
- Experience with Agentic Workflows (Multi-agent systems like AutoGPT or CrewAI).
- Experience with AI-driven code migration or refactoring tools.
- Experience in Fintech or Startups where rapid scaling was required.
