Description

In this role, you will work closely with various teams to rapidly deploy innovative GenAI features. Your day-to-day responsibilities will involve designing LLM workflows, building user-friendly interfaces, and mentoring fellow engineers to enhance their GenAI skills.

Requirements

• •Professional software background
• •3+ years building production systems
• •Proven experience with LLM stacks
• •Prompt engineering, embeddings & vector DBs
• •LangChain/LlamaIndex, RAG design
• •Model selection & cost optimisation
• •Practical knowledge of LLM workflow orchestration
• •Process automation tools (e.g., n8n)
• •Proficient in Python and TypeScript
• •Using modern frameworks like FastAPI, Node.js, and React
• •Comfortable running ML workloads on AWS
• •SageMaker, Bedrock, Lambda, Step Functions, CDK/Terraform
• •Familiar with CI/CD, Docker, test-driven development
• •Observability (logs, traces, cost dashboards)
• •Strong communication skills for pair-programming
• •Technical coaching
• •Evidence of exceptional achievement
• •Scaling personal projects, published research, competitive rankings
• •Motivation to grow

Tasks

• •Collaborate with cross-functional teams to deploy GenAI features quickly
• •Design and implement LLM workflows, including prompt templates and RAG pipelines
• •Build engaging interfaces using TypeScript, React, and Next.js
• •Develop robust LLM-powered backends with Python
• •Transform prototypes into reliable, production-ready services
• •Establish automated evaluations and human-in-the-loop reviews for quality and safety
• •Document recurring patterns as platform components in internal playbooks
• •Coach fellow engineers through office hours, code reviews, and lightning talks

Tools & Technologies

Benefits