AI Engineer Intern

About GoTyme

GoTyme is a joint venture between the Gokongwei Group, one of the biggest conglomerates in the Philippines, and the Singapore-headquartered digital banking group Tyme. This venture combines the trusted Gokongwei brand, customer base, and distribution ecosystem with Tyme’s globally proven digital banking technology and hands-on experience building South Africa’s leading digital bank, TymeBank, one of the fastest-growing digital banks in the world today.

At GoTyme, we have embarked on a journey to democratize financial services and bring next-level banking to the Philippines. We seek individuals who share our belief that the game is worth changing, to join our growing team of GoTymers as we build, launch, and scale a bank that empowers all Filipinos to navigate a path to financial freedom.

Why this role exists

Join a GenAI pod that designs and ships lightweight micro-apps, copilots, and decision helpers for internal high-impact teams. You’ll help move features from prototype → production quickly, improving decisions and workflows with modern LLMs and agentic workflows.

What you’ll do

Onboarding & Foundations

• Shadow pod rituals; set up repos, dev env, and access.
• Learn house patterns for prompts, evals, and secure coding in a regulated context.

Prompt Engineering & Experiments

• Craft, test, and iterate prompts for models such as GPT-5, Claude 4, and Gemini.
• Log results; identify failure modes (bias, hallucination, latency); propose mitigations and patterns for the wiki.

Rapid Prototyping

• Build chatbots, unstructured data analyzers, extractors, agentic workflows—in Python with modern agent orchestration tools.
• Spin up n8n automations with integrations to platforms like Databricks and Confluence.

Monitoring & Iteration

• Instrument basic telemetry (latency, cost, success rate) and user feedback capture with tools such as MLFlow and Databricks Evals.
• Tune prompts/graphs; swap models when metrics regress.

Collaboration & Knowledge-Share

• Pair with different departments such as Ops/Product/Risk to translate pain-points into scoped tasks.
• Run short demos to demonstrate developed features; write concise docs/readmes non-engineers can follow.

Must-have

• Final-year students in Computer Science/Engineering/Data Science (or similar) or recent graduate.
• Python proficiency; comfort with notebooks and scripting.
• Familiar with one GenAI SDK (OpenAI, Anthropic, Google, Hugging Face, etc.).
• Basic web/API skills (HTTP/REST, JSON, simple React or vanilla JS).
• Git fluency and light data wrangling (Pandas or SQL).
• Evidence of initiative (side projects, coursework, hackathons).
• Clear written and spoken English.

Nice-to-have (great to learn here if not yet!)

• AI Orchestration Framework (stateful agents, tool orchestration) such as LangGraph and CrewAI.
• MCP (Model Context Protocol): building/consuming MCP tools/servers.
• RAG basics (chunking, embeddings), vector DBs (FAISS/Chroma/Pinecone).
• Cloud exposure (AWS/GCP/Azure), containers, CI basics.
• Front-end polish (React, Tailwind) for quick internal UIs.
• Fintech/regulatory awareness helpful (secure coding, data privacy).

What you’ll learn (fast)

• Designing agentic workflows that ship: tool choice, recovery paths, evals.
• Wiring MCP tools to give models safe, auditable access to enterprise resources.
• Measuring and improving real-world quality/cost/latency under production constraints.
• Secure coding in a regulated environment (secrets, PII handling, logging hygiene).
• Communicating technical trade-offs to non-technical stakeholders.