GenAI Engineer intern at GoTyme developing micro-apps and decision helpers. Focused on improving internal workflows using modern LLMs and agentic workflows.
Responsibilities
Join a GenAI pod that designs and ships lightweight micro-apps, copilots, and decision helpers for internal high-impact teams.
Help move features from prototype → production quickly, improving decisions and workflows with modern LLMs and agentic workflows.
Shadow pod rituals; set up repos, dev env, and access.
Learn house patterns for prompts, evals, and secure coding in a regulated context.
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.
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.
Instrument basic telemetry (latency, cost, success rate) and user feedback capture with tools such as MLFlow and Databricks Evals.
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.
Requirements
Final-year student in CS/Engineering/Data Science (or similar) or recent grad.
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).
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