Senior GenAI Platform Engineer - AWS Bedrock

Fractal Analytics; Massachusetts; Sur place; USD 120 000 - 150 000; Plein temps

Avantages offerts par ce poste

Health benefits

401(k) plan

11 paid holidays

12 weeks parental leave

Flexible PTO

Résumé du poste

Fractal Analytics is hiring an onsite Senior Gen AI Engineer in Cambridge, MA. The role focuses on building scalable, secure GenAI platforms and agentic AI applications on AWS, with hands-on work across orchestration, governance, and cloud-native microservices.

You will work with Amazon Bedrock to drive LLM inference and model integrations, developing reusable APIs, SDKs, accelerators, and reference architectures for enterprise RAG systems and multi-agent workflows.

Qualifications

• 8-10 years of software engineering experience.
• 3+ years in GenAI or AI solution development.
• Strong Python proficiency and AWS experience.
• Experience with LLMs, model orchestration, and prompt engineering.

Responsabilités

• Design, develop, and maintain scalable GenAI platforms on AWS.
• Architect multi-agent AI solutions and orchestration frameworks.
• Build enterprise-grade RAG solutions using embeddings and vector databases.
• Develop AI applications leveraging Bedrock for model orchestration and prompts.
• Create evaluation, benchmarking, governance, and security frameworks.
• Develop observability with telemetry, monitoring, tracing, and dashboards.
• Design cloud-native microservices and APIs using Python and CI/CD pipelines.

Connaissances

GenAI

Agentic AI

Python

AWS

Cloud architecture

Kubernetes

CI/CD

Observability

Security governance

Outils

AWS Bedrock

Terraform

Docker

OpenSearch

ECS/EKS

Description du poste

Fractal Analytics is hiring an onsite Senior Gen AI Engineer in Cambridge, MA. The role focuses on building scalable, secure GenAI platforms and agentic AI applications on AWS, with hands-on work across orchestration, governance, and cloud-native microservices.

You will work with Amazon Bedrock to drive LLM inference and model integrations, developing reusable APIs, SDKs, accelerators, and reference architectures for enterprise RAG systems and multi-agent workflows.