Senior ML/AI Engineer (LLM)

**About the Role
**We are hiring a Senior ML/AI Engineer to join a small, senior, fully dedicated team building an AI-powered content generation platform for a US-based client. The platform uses LLMs to generate rich, structured content — including interactive components and media — and integrates with the client's existing systems.

Content safety is a core constraint of the product, not an afterthought: every generation passes through guardrails that validate vocabulary, tone, and subject matter before anything reaches an end user. This role is where most of that work happens.

What You'll Do

• Build the LLM generation pipeline: prompt construction from structured inputs, model calls, and structured output that maps to renderable content components

• Design and implement safety filters and guardrails: content moderation, tone and vocabulary validation, and output checks before content is shown to users

• Build output evaluation: eval sets, automated quality scoring, regression testing on prompt and model changes, and human-review workflows

• Implement retrieval (RAG) so generated content is grounded in the client's reference material

• Build and operate the AWS serverless services behind the pipeline: Lambda, Step Functions, API Gateway, SQS/EventBridge, DynamoDB/S3

• Build the image generation pipeline for in-product graphics, deployed within the client's AWS environment (Bedrock image models or SageMaker-hosted alternatives); contribute to a longer-term generative video roadmap

• Handle production LLM concerns: streaming, caching, retries, rate limits, cost monitoring, and observability

• Collaborate daily with the team lead, full-stack engineers, and the client's internal teams

Required Qualifications

• 5+ years of software engineering experience, with 1–2+ years shipping production features on top of LLMs (not just prototypes)

• Strong Python; comfortable contributing in TypeScript/Node when the pipeline touches shared services

• Hands-on experience with AWS Bedrock (model access, IAM, invoking hosted models in production) — experience with other LLM APIs (Anthropic, OpenAI, Google Vertex) is valuable but not a substitute

• Strong grasp of function calling / structured outputs (JSON schema) for reliable, renderable generation

• Production experience with image generation (Bedrock image models, Stable Diffusion, or similar), ideally deployed inside a client's cloud environment rather than via external APIs

• Experience building AWS serverless architectures: Lambda, API Gateway, Step Functions, and event-driven patterns