Senior AI Platform Infrastructure Engineer

DXC Luxoft; United States; Remote; USD 150,000 - 190,000; Full time

Job summary

DXC Luxoft partners with a top-tier Hedge Fund to scale an AI agent platform running 1,500+ agents in production. We seek Senior Platform Engineers to build across the stack—from infrastructure to the agent framework and MCP tools.

You will own Kubernetes/EKS on AWS, secure inter-agent communication, multi-tenant memory models, and the CI/CD pipelines and observability tooling that keep the system reliable at scale.

Qualifications

• Experience building production-grade agent platforms.

Responsibilities

• Own both agent and MCP tool layers and the Kubernetes/AWS platform.

Skills

Agent SDKs

Prompting

Context and memory

Kubernetes

AWS

CI/CD

Terraform

GitOps

Python

Security policies

Multi-tenant security

Event-driven systems

Tools

Terraform

CloudFormation

Pulumi

ArgoCD

GitHub Actions

Jenkins

Datadog

SQS

Kafka

Job description

Project description

Our partner, a top tier Hedge Fund, is expanding their AI agent platform. The platform runs 1,500+ agents in production across the firm. We are looking for Senior Platform Engineers to build across the whole stack, from the infrastructure to the agents and MCP tools that run on it. In the next phase agents securely work together.

Responsibilities

• You'll join the team that runs and own both layers: the agents, MCPservers and tools our users rely on, and the Kubernetes/AWS platform with event-driven systems underneath them. From there, you'll build what lets agents work as a team: secure communication between agents, agents that manage other agents, shared memory with the right access controls, and the evals that keep it reliable at scale.

SKILLS

• Hands-on experience building agents in production with agent SDKs (e.g. Claude Agent SDK, Codex SDK): tool use, context and memory, prompting
• Experience building and running MCP servers and toolsDeep hands-on Kubernetes (EKS preferred): cluster design, networking (CNI, service mesh), RBAC and security policies
• Strong AWS: VPC architecture, IAM, EKS/ECS, networking and securitygroups Infrastructure as code (Terraform, CloudFormation or Pulumi), GitOps and CI/CD (ArgoCD, GitHub Actions, Jenkins)
• Container architectures for multi-tenant, security-sensitive workloads
• Event-driven systems: queues and pub/sub (e.g. SQS, Kafka), webhooks,async workers, retries and idempotency
• Production observability and incident response (Datadog or similar)
• Strong python

Nice to have

• Agent-to-agent (A2A) protocols and multi-agent orchestration
• JavaScript/TypeScript and Go
• UI / front-end experience (a plus for one of the three roles: agentmanagement console)
• Auth: OAuth 2.0 / OIDC, identity federation and SSO, delegated (on-behalf of) tokens
• Agent evaluation: test sets, graders, regression gates
• Permission-aware search, retrieval or shared memory
• Securing autonomous or long-running AI workloads at scale
• Financial or regulated environments, compliance-aware infrastructur