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AWS DevOps Engineer / AI Platform Engineer (Hybrid Onsite)

GSK Solutions Inc.Sinking Spring, PA🇺🇸United States

Why this role stands out

Advance your career as an AWS DevOps Engineer by building and scaling critical AI platforms within a renowned organization offering hybrid flexibility. You'll thrive in this role if you possess strong AWS and DevOps expertise and are eager to contribute to innovative technology solutions in a collaborative environment. Apply now to leverage your skills and gain valuable experience.

Quick overview

SeniorityMid Senior

Work modeHybrid

LocationSinking Spring, PA, United States

AWSConfluenceLLMTerraformAgileMicrosoft TeamsCI/CDLangChainIAM

Job description

Job Title

AWS DevOps Engineer / AI Platform Engineer (Hybrid Onsite)

Location

Reading, PA

Duration

6 Months

Interview Type

Virtual / In-Person

Note

Hybrid 2-3 days/wk at client office
Is your candidate willing to relocate for position

Description

Requirements

Experience: 8+ years in Platform Engineering, DevOps, or Site Reliability Engineering (SRE).
Cloud Expertise: Deep proficiency in AWS (IAM, CloudWatch, Bedrock, Lambda).
Observability Tools: Proven experience with Dynatrace, Jaeger, or Honeycomb, and distributed tracing standards.
AI/LLM Interest: Familiarity with the LLM lifecycle, including prompt execution, token usage, and frameworks like LangChain or AgentCore.
Automation: Advanced experience with Terraform and CI/CD pipeline design.
Collaboration: Experience working in an Agile environment with integrated tools like Microsoft Teams and Confluence.

User this when submitting candidates:

Also please check if the next candidate has some experience with at least 50% of below items:

Implementation of Agents on Agentcore runtime
Implementation of Agentic SDLC in Agentcore
Understanding of Strands or any other Agentic AI framework like Langraph, Langchain or Crew AI
Implementation of Bedrock Knowledge Base
Implementation of Knowledge Graph
Implementation of MCP servers in Agentcore
Implementation of Agentcore Gateway
Implementation of Agentcore Identity
Implementation of Agentic AI Observability
Implementation of Agentcore Evaluations
Implementation of AWS Bedrock
Implementation of AWS Bedrock Inference Profile
Implementation of AWS Sagemaker
AWS Services (Cloud) in General
Terraform

Deliverables

Observability

Assess CloudWatch, X-Ray, Bedrock logging, AgentCore traces vs. agentic workflow requirements; produce gap analysis, Setup observability in Dynatrace
Design post-deployment validation pipeline for agents & MCP servers (deployment health + tool registration checks)
Implement distributed tracing & structured logging: LLM decisions, tool selections, sub-agent calls, MCP interactions
Evaluate LangFuse / LiteLLM proxy vs. AWS-native; deliver target-state observability architecture recommendation

Cost Tracking & TCO

Extend tagging taxonomy to cover agent runtimes, MCP servers, vector DBs, Bedrock token consumption per namespace
Design cost visibility model: aggregate agent, MCP, vector DB, and Bedrock token costs per team/department
Build CloudWatch (or equivalent) dashboards for per-team spend; configure AWS Budgets with alerting thresholds
Automate cost reports delivered via email / Microsoft Teams; implement anomaly detection rules

Monitoring & Alerting

Define P1–P4 alerting rules: deployment failures, runtime errors, tool invocation failures, MCP connectivity issues
Integrate alert notifications to Microsoft Teams channels and email; route by resource ownership tags
Author runbooks linked to every alert; publish in Confluence for developer self-service resolution
Evaluate AWS-native vs. third-party monitoring stack; deliver recommendation aligned to observability architecture

Security & Access Control

Assess current IAM + tagging approach for multi-team isolation; identify scalability gaps and risks
Evaluate Cedar policy engine (AgentCore) for fine-grained tool access control; document enterprise-scale gaps
Design scalable ABAC-based identity model for multi-team isolation without IAM policy sprawl; deliver Terraform modules

Top Skills

Skill	Experience required
Platform Engineering / DevOps / SRE	8+ years
AWS Cloud Services	7+ years
Observability Tools	7+ years
AI/LLM Platforms	7+ years
Terraform / CI-CD	7+ years
Agile Collaboration	7+ years