Senior AI Platform Engineer

About the Role  

Kaleris is a global leader in supply chain execution, focused on accelerating the transformation of digital supply chain for industrial and finished goods shippers and carriers by combining best-in-class solutions for industry-specific challenges tied to yard management, shipment visibility, and asset management, across rail, truck, and multi-mode transportation.   

Our cloud-based solutions connect shippers, carriers, and drivers to the Kaleris platform where visibility across multiple modes and nodes are connected and deliver powerful analytics and second to none, enterprise-level execution.   

Many of the world's largest shippers rely on Kaleris solutions for mission-critical workflows to achieve the confidence and clarity necessary to make moves ahead of the curve. Kaleris is backed by Accel-KKR, a leading technology-focused private equity firm with deep domain expertise in supply chain management software and solutions.

Kaleris is seeking a Senior AI Platform Engineer to join our engineering team. The rapid integration of AI tools accelerates application development and is creating new opportunities across the business — teams are building software faster than ever, and the need to get those applications reliably running and available to the people who need them has never been greater. In this role, you will be a hands-on contributor building the SDLC platform and toolchain that bridges the gap: taking AI-generated and human-authored software and ensuring it can be properly built, validated, secured, deployed, and operated at scale. You will work alongside Software Engineers, DevOps Engineers, Product Management, and QA teams to design and deliver a robust developer platform — from CI/CD pipelines and self-service tooling to observability and security automation — that makes it practical for the whole of Kaleris to ship quality software consistently. This role requires a strong software engineering background and hands-on familiarity with the full development lifecycle. You must be a pragmatic problem-solver, an effective communicator, and someone who can deliver scalable solutions that improve how Kaleris builds and ships software.
 

Responsibilities

• Design, build, and maintain AI-powered capabilities across the SDLC, including intelligent agents for proactive alerting, automated diagnostics, and self-healing workflows.

• Partner with engineering teams to identify and automate high-friction parts of the development lifecycle — from Jira and GitHub workflows through CI/CD, testing, security scanning, and deployment.

• Develop and operate self-service developer tooling that reduces toil and accelerates engineering velocity across Kaleris product teams.

• Integrate and maintain CI/CD pipelines using GitHub Actions, enforcing quality gates (PR reviews, green build, Jira traceability, QA approval, security scans).

• Embed security tooling (BlackDuck, Wiz Code, BURP Suite, 1Password) and monitoring platforms (Sumologic, PagerDuty) into automated workflows.

• Build and manage IaC-driven infrastructure on AWS and/or Azure using Terraform, OpenTofu, and Helm, deploying to Kubernetes (EKS/AKS) via Argo CD or Spacelift.

• Champion engineering effectiveness through measurement — instrument and improve DORA metrics using tools such as Jellyfish.

• Drive adoption of AI tooling and SDLC best practices across Kaleris engineering, providing documentation, enablement, and mentoring.

• Ensure governance and compliance standards are upheld across the SDLC — including access controls, audit trails, and policy enforcement within CI/CD pipelines and deployment workflows.

• Carry personal responsibility for high-quality changes delivered in an agile manner. 

Requirements

• Minimum 5 years of Software Engineering or DevOps experience, with demonstrable familiarity with the full development lifecycle (SDLC) and working alongside software development teams.

• Demonstrated, hands-on experience actively integrating large language model (LLM) tools or agents into real development or operational workflows — we are looking for engineers who have been genuinely building with and benefiting from LLMs, distinct from traditional ML/data science backgrounds.

• Hands-on experience building or operating CI/CD pipelines, preferably GitHub Actions.

• Proficiency in at least one scripting/programming language used for automation — TypeScript/JavaScript preferred (the native option for GitHub Actions), with Python also valued.

• Experience with Infrastructure as Code tools (Terraform, OpenTofu, Helm).

• Familiarity with cloud platforms (AWS and/or Azure) and container orchestration (Kubernetes).

• Demonstrated ability to work in or closely alongside software development teams.

• Fluent in the English language.

Additional skills and experience

• Familiarity with DevSecOps tooling: SAST, DAST, SCA, and secrets management.

• Experience with observability and monitoring platforms (Sumologic, PagerDuty, or OTEL-compatible tooling).

• Knowledge of engineering metrics frameworks (DORA, Jellyfish, or similar).

• Experience with GitOps workflows and deployment tools (Spacelift, Argo CD).

• A passion for keeping pace with AI and platform engineering trends and applying them pragmatically.

• Experience working in a global organization across multiple time zones and cultures.

The duties and responsibilities described are not a comprehensive list and additional tasks may be assigned from time to time or the scope of the position may change necessary to business demands.