About this role

Talend is hiring a senior-level AI Infrastructure Engineer in the machine learning function based in King of Prussia, PA | Boston, MA. The posting calls out experience with Python, AWS, Docker, Terraform.

Role: AI Infrastructure Engineer
Function: machine learning
Level: senior
Track: Individual contributor
Location: King of Prussia, PA | Boston, MA
Posted: Jul 8, 2026

AI Summary

Own production AI infrastructure on AWS, building and operating cloud platforms for AI agents and LLMs. Requires deep Terraform, AWS (Bedrock, Lambda, ECS/Fargate), IAM security expertise, CI/CD proficiency, and Python scripting skills. Must drive infrastructure reliability, cost optimization, and observability independently.

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Job description

from Talend careers

The ideal candidate will have hands-on experience owning production infrastructure, with deep proficiency across AWS and the modern cloud engineering stack: Infrastructure as Code: You have strong hands-on Terraform experience. You version-control infrastructure the same way you version-control code. AWS Platform Depth: Deep AWS experience across Bedrock (model invocation, agents), Lambda, API Gateway, ECS/Fargate, App Runner, IAM, VPC, S3, CloudWatch, and X-Ray. Bedrock AgentCore exposure is a strong plus. Security Mindset: You understand the AWS IAM model deeply: roles, policies, SCPs, permission boundaries, and cross-account trust. You instinctively scope to least privilege. CI/CD: You build pipelines that deploy infrastructure and application code reliably. GitHub Actions, CodePipeline, or equivalent. You know how to roll back safely. Observability: Experience with OpenTelemetry, CloudWatch Logs Insights, and distributed tracing. You care about visibility into what AI systems are actually doing and what they cost. Python: Comfortable with Python for scripting, Lambda functions, and lightweight automation. You don't need to be an ML engineer, but you can read and modify agent code. Containers: Comfortable with containerized workloads (Docker, ECS, Fargate, App Runner). Experience running long-running agent processes or streaming inference endpoints is a plus. Data Infrastructure: You understand vector search infrastructure and are comfortable operating OpenSearch clusters for semantic retrieval. Experience with RAG pipeline data stores preferred. Ownership: You close the loop. You don't just provision infrastructure, you monitor it, cost-optimize it, and improve it without being asked. Comfort with Ambiguity: AI infrastructure is still being invented. You are energized by ambiguity and comfortable writing the runbook that didn't exist before you joined. Communication: Able to explain an IAM boundary decision or a rate-limiting architecture to an AI engineer or a business stakeholder equally well. Security and Governance Mindset: You think about what happens when things fail, when costs spike, when an agent calls an endpoint it shouldn't. You build guardrails proactively.