Haystack
← Back to Jobs
Technology
GS

AWS DevOps Engineer / AI Platform Engineer (Hybrid Onsite)

GSK Solutions Inc.Sinking Spring, PA🇺🇸United StatesPosted Sep 25, 2026

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

Seniority
Mid Senior
Work mode
Hybrid
Location
Sinking Spring, PA, United States
Posted
2 days ago
AWSAgileConfluenceLLMTerraform

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

Recruiter

Contact: Sameer - - Seven one nine - two three nine - Five five five five

Similar jobs

Browse related jobs

Apply now