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We are looking for a backend engineer who can design, build, and operate highly reliable Node.js services on AWS that enable generative‑AI capabilities across our products and internal workflows.
You will create scalable APIs, data pipelines, and serverless architectures that integrate large‑language‑model (LLM) services such as Amazon Bedrock, OpenAI, and open‑source models, enabling teams to safely and efficiently leverage generative AI.
Who You Are:
You have experience building Retrieval‑Augmented Generation (RAG) systems or knowledge‑base chatbots.
You're Hands‑on with vector databases such as Pinecone, Chroma, or pgvector on Postgres/Aurora.
Have AWS certification (Developer, Solutions Architect, or Machine Learning Specialty).
Experience with observability tooling (Datadog, New Relic) and cost‑optimization strategies for AI workloads.
Background in microservices, domain‑driven design, or event‑sourcing patterns.
What Youll Actually Be Doing
Design and implement REST/GraphQL APIs in Node.js/TypeScript to serve generative‑AI features such as chat, summarization, and content generation.
Build and maintain AWS‑native architectures using Lambda, API Gateway, ECS/Fargate, DynamoDB, S3, and Step Functions.
Integrate and orchestrate LLM services (Amazon Bedrock, OpenAI, self‑hosted models) and vector databases (Amazon Aurora pgvector, Pinecone, Chroma) to power Retrieval‑Augmented Generation (RAG) pipelines.
Create secure, observable, and cost‑efficient infrastructure as code (CDK/Terraform) and automate CI/CD with GitHub Actions or AWS CodePipeline.
Implement monitoring, tracing, and logging (CloudWatch, X‑Ray, OpenTelemetry) to track latency, cost, and output quality of AI endpoints.
Collaborate with ML engineers, product managers, and front‑end teams in agile sprints; participate in design reviews and knowledge‑sharing sessions.
Establish best practices for prompt engineering, model evaluation, and data governance to ensure responsible AI usage.

This is not your typical leadership role. If you’re looking to manage tasks, run standups, and stay above the code - this position probable isn’t for you. But if you want to build systems, shape engineers, and redefine how teams operate in the age of AI - keep reading. ?What we’re actually building At Chargeflow, we’re building systems that don’t just process data - they make decisions. Real-time. At scale. Under uncertainty. Fraud evolves fast. So our systems, and our engineers, need to evolve faster. This is where you come in. What you’ll actually do
* You’ll lead a team - but you’ll also build with them
* You’ll make architectural decisions that directly impact how the system scales and behaves
* You’ll own critical parts of the system - not just people
* You’ll turn ambiguity into direction (for both product and engineering)
* You’ll raise the bar: in code quality, system design, and how the team thinks
* You’ll embed AI into how the team works - not as a tool, but as leverage
* You’ll help strong engineers become exceptional