Principal DevOps AI IRC303057

GlobalLogic; Bogotá; Presencial; COP 187.447.000 - 281.171.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Competitive salary

Global exposure

Professional development

Descripción de la vacante

GlobalLogic seeks an AI Systems Engineer to own the infrastructure, deployment, and reliability of production-grade agentic AI systems. You will provision and secure AWS Bedrock environments, build scalable pipelines, and optimize costs while collaborating with AI engineers and executives.

The role combines cloud infra engineering with AI system operations. You will work directly with Bedrock AgentCore, Lambda, API Gateway, and ECS/Fargate, ensuring performance and governance across data,

Formación

• Ownership mindset: you own infra end-to-end, monitor, cost-optimize and improve without prompting.
• Comfort with ambiguity: AI infra is evolving; you write the runbook as you go.
• Security-minded: you design guardrails and least-privilege access proactively.

Responsabilidades

• Design and maintain infrastructure-as-code for AI workloads (Terraform).
• Own deployment, configuration, and scaling of AWS Bedrock AgentCore environments.
• Architect secure IAM policies and cross-account access patterns.
• Build and maintain CI/CD pipelines for infrastructure and agent updates.
• Instrument AI systems with OpenTelemetry, CloudWatch, and X-Ray for observability and costs.

Conocimientos

Ownership

Ambiguity tolerance

Communication

Security mindset

Herramientas

Terraform

AWS Bedrock

Lambda

API Gateway

ECS/Fargate

IAM

OpenTelemetry

CloudWatch

X-Ray

Descripción del empleo

AWS (CodeCommit), AWS Bedrock, CI/CD Tools, Docker, github actions, MCP, opentelemetry, Python

Beyond technical skills, we’re looking for someone who brings:

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.

Requirements

As an AI Systems Engineer, you will own the infrastructure, deployment, and reliability of production-grade agentic AI systems that power the next generation of intelligent automation at Project Reporting to the Global Head of AI Strategy, Policy, and Governance, you will operate at the intersection of cloud infrastructure engineering and AI systems, provisioning, securing, and scaling the AWS environments that make our AI pipelines run reliably and cost-efficiently.

What makes this role interesting?

Ownership: Own real infrastructure. This is not a role where you configure demos, you will provision, harden, and operate the AWS environments that run client AI agents at scale.
Frontier Stack: Work directly with AWS Bedrock AgentCore, a capability that most cloud engineers are only beginning to encounter. You’ll be among the first teams operationalizing it in production.
High Impact: Small team, direct line to executive leadership, real decisions.

Here’s how you’ll be making an impact:

• IaC and Cloud Provisioning: Design and maintain infrastructure-as-code (Terraform) for all AI workloads: Bedrock agents, AgentCore runtimes, Lambda functions, API Gateway endpoints, and supporting data services.
• AWS Bedrock AgentCore: Own deployment, configuration, and scaling of AWS Bedrock AgentCore environments, including model invocation routing, session management, and memory backends.
• Security and IAM: Architect secure, least-privilege IAM policies for agent runtimes, MCP integrations, cross-account access patterns, and service-to-service authentication.
• CI/CD Pipelines: Build and maintain CI/CD pipelines (GitHub Actions, AWS CodePipeline) for agentic workloads, covering infrastructure changes, Lambda deployments, and agent configuration updates.
• Observability and Cost Management: Instrument AI systems with OpenTelemetry, CloudWatch, and X-Ray. Own observability strategy: traces, metrics, cost dashboards, and alerting across agent pipelines.
• Networking: Manage networking topology for AI workloads: VPC design, PrivateLink, security groups, and egress controls to ensure data never leaves governed boundaries unexpectedly.
• Data Infrastructure: Build and operate the data infrastructure supporting agents: OpenSearch for semantic search and vector retrieval, and S3 lifecycle policies for knowledge artifact storage.
• Collaboration: Collaborate with AI engineers on MCP server deployments, containerized agent runtimes (ECS/Fargate), and performance tuning to hit latency and cost targets.

Job responsibilities

We’re looking for a teammate with:
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.

What we offer

• Exciting Projects: Come take your place at the forefront of digital transformation! With clients across all industries and sectors, we offer an opportunity to work on market-defining products using the latest technologies.
• Collaborative Environment:Expand your skills by collaborating with a diverse team of highly talented people in an open, laidback environment — or even abroad in one of our global centers or client facilities!
• Work-Life Balance:GlobalLogic prioritizes work-life balance, which is why we offer flexible work schedules. We offer you the best quality of work life so that you exceed the expectations of our clients, while achieving your professional and personal ambitions.
• Professional Development:Our dedicated Learning & Development team regularly organizes English classes, professional certifications, and technical and soft skill trainings. We also offer the chance to travel internationally
• Excellent Benefits:We provide our employees with competitive salaries, family medical insurance, extended paternity leave, annual performance bonuses, and referral bonuses.

About GlobalLogic

GlobalLogic, a Hitachi Group Company, is a trusted digital engineering partner to the world’s largest and most forward-thinking companies. Since 2000, we’ve been at the forefront of the digital revolution – helping create some of the most innovative and widely used digital products and experiences. Today we continue to collaborate with clients in transforming businesses and redefining industries through intelligent products, platforms, and services.