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We are an IT Solutions Integrator/Consulting Firm helping our clients hire the right professional for an exciting long-term project. Here are a few details.

Requirements

About the
Role

Our client is seeking
a highly skilled
AI DevOps Engineer
to design, build, and operate
scalable, secure, and production-grade infrastructure supporting modern AI
platforms and LLM-powered applications.

This role sits
at the intersection of
DevOps, Platform Engineering, Site Reliability
Engineering (SRE), and AI Infrastructure
, enabling high-performance AI
systems, agent-based workflows, and enterprise AI platforms within a regulated
financial services environment.

The ideal
candidate will have strong expertise in
Kubernetes, Terraform, cloud
infrastructure, automation, and AI platform operations
, along with
experience supporting modern AI/LLM workloads in production environments.

Key
Responsibilities

• 
  Design, deploy, and manage scalable infrastructure
  for AI and LLM-based applications in production environments.
• 
  Build and maintain Infrastructure-as-Code (IaC)
  using tools such as Terraform for secure, repeatable, and auditable
  deployments.
• 
  Deploy, manage, and scale containerized
  environments using Kubernetes with a focus on high availability and
  reliability.
• 
  Implement DevOps, Platform Engineering, and SRE
  best practices to improve system reliability, scalability, and operational
  efficiency.
• 
  Support AI platform services for model serving,
  inference, experimentation, and evaluation workflows.
• 
  Deploy and maintain infrastructure supporting AI
  agents, orchestration frameworks, and LLM runtime dependencies.
• 
  Design and manage vector database infrastructure
  including Pinecone, Weaviate, or PostgreSQL with pgvector for RAG and
  semantic search use cases.
• 
  Enable AI developer platforms and tooling for
  engineering teams building AI-powered applications.
• 
  Implement monitoring, alerting, logging, and
  incident response processes for mission-critical AI systems.
• 
  Collaborate with security, compliance, and
  governance teams to ensure adherence to regulatory and enterprise security
  standards.
• 
  Continuously improve automation, developer
  experience, and operational processes for AI infrastructure environments.

Required
Qualifications

• 
  Bachelor’s degree in Computer Science, Engineering,
  or equivalent practical experience.
• 
  Proven experience as a DevOps Engineer, Platform
  Engineer, or Site Reliability Engineer (SRE).
• 
  Strong hands-on experience managing large-scale
  production infrastructure.
• 
  Expertise with Terraform and Infrastructure-as-Code
  (IaC) methodologies.
• 
  Strong experience deploying and operating
  Kubernetes-based environments.
• 
  Experience supporting infrastructure for AI
  platforms or LLM-based applications.
• 
  Strong understanding of automation, scalability,
  reliability, and cloud-native architectures.

Preferred
Qualifications

• 
  Experience supporting production-grade LLM
  applications and AI agent workloads.
• 
  Hands-on experience with vector databases such as
  Pinecone, Weaviate, or pgvector.
• 
  Experience building or supporting AI tooling and
  internal AI developer platforms.
• 
  Knowledge of observability, monitoring, capacity
  planning, and reliability engineering for AI/ML systems.
• 
  Experience working within financial services or
  other highly regulated industries.
• 
  Strong communication and cross-functional
  collaboration skills.

Benefits