Manager _Forward Deployment Engineer , DevOps, AI Deployment

Manager Forward Deployment Engineer (DevOps, AI Deployment)

AI Deployment & DevOps Engineering | Forward Deployed Engineering

Experience Required

9 to 16 years, including team and delivery leadership.

Job Summary

An engineering leader who owns how AI solutions are deployed into enterprise environments across a set of accounts. You will own delivery, standards, and the customer relationship, and set the direction for building, securing, and operating AI applications in production on AWS.

Key Responsibilities

• Own the delivery of AI deployment work across your accounts, including scope, quality, timelines, and standards.
• Set direction and standards for CI/CD, Infrastructure as Code, cloud architecture, security, and MLOps/LLMOps.
• Lead the responsible integration of AI solutions into legacy and regulated enterprise environments at scale.
• Act as senior escalation and decision-maker on complex or high-stakes deployments.
• Build reusable accelerators and patterns that raise deployment quality across the practice.
• Build, lead, and grow the team through hiring, coaching, and development.
• Own senior customer relationships and communicate progress, risks, and value.
• Surface delivery friction and product gaps to leadership as structured field intelligence.

Required Qualifications

• Extensive DevOps or platform engineering experience, including leading teams and owning delivery at scale.
• Current depth in AWS, Kubernetes, CI/CD, and Infrastructure as Code.
• Proven enterprise integration experience with security, identity, and governance constraints.
• Proven ownership of delivery outcomes and senior customer relationships.
• A clear strategy for productionising AI at scale (LLMOps/MLOps), including responsible AI, backed by delivery experience.
• Strong leadership and communication skills; decisive under pressure.
• Mandatory: AWS, DevOps, or GenAI certification (at least one) is required.

Preferred Qualifications

• AWS enterprise-scale architecture experience.
• Enterprise AI and data platforms (Palantir Foundry, Databricks, Snowflake).
• A background in consulting or managed services.
• Experience in regulated industries.
• A leadership or delivery certification (e.g., PMP, SAFe).
• AWS Certified Solutions Architect Professional and/or AWS Certified DevOps Engineer Professional.

Technical Skills & Tools

• Cloud & platform: AWS (Bedrock, SageMaker, EKS, Lambda, IAM), Kubernetes
• Delivery & IaC: CI/CD (GitHub Actions, GitLab CI, ArgoCD), Terraform
• AI productionisation: LLMOps / MLOps, model serving, evaluation, responsible AI, governance
• Security & compliance: IAM, secrets management, network security, data governance
• Good to have: Enterprise AI and data platforms (Palantir Foundry, Databricks, Snowflake), MLflow

Soft Skills & Competencies

• Leadership of both a team and a customer relationship.
• Stakeholder and customer management.
• Decisive under pressure.
• Coaching and people development.