Consultant (Enterprise AI Implementation Specialist)
About the Role
We are seeking a highly skilled Consultant to lead the configuration integration and enterprise-grade adoption of Devinan autonomous AI software engineering platform. This role involves working with engineering DevOps security architecture and business teams to ensure Devin is deployed securely optimized for productivity and aligned with our software delivery processes.
The consultant will act as the primary SME for defining best practices building governance frameworks enabling teams and accelerating the platforms impact across the enterprise.
Key Responsibilities
1. Platform Setup & Integration
Lead the configuration and environment setup of in enterprise settings.
Integrate Devin with existing developer tools:
oGitHub
oCI/CD pipelines (Jenkins GitHub Actions Azure DevOps etc.)
oJira/ServiceNow
oInternal code repositories and artefact stores
Configure access controls role-based permissions and secure networking.
2. Enterprise Architecture & Security
Work with architecture and cybersecurity teams to ensure:
oData security compliance and privacy alignment
oProper isolation of environments
oSecure API usage and credential management
Create governance models for safe and responsible AI use.
3. Workflow Design & Process Enablement
Define how Devin integrates into SDLC DevOps QA and engineering workflows.
Develop templates SOPs and best practices for:
oAutonomous task execution
oCode generation & review
oAutomated testing & deployment
oObservability & quality checks
Enable multi-team adoption with operational readiness plans.
4. Change Management & Enablement
Conduct enablement sessions hands-on training and workshops for engineering teams.
Build documentation user guides and troubleshooting playbooks.
Support early-stage pilots use case discovery and enterprise-scale rollout.
6. Technical Leadership & Advisory
Serve as the subject matter expert for AI-driven engineering workflows.
Provide recommendations on scaling DevOps platform engineering and automated development using AI.
Collaborate with product and engineering leaders on roadmap alignment.
Required Qualifications
6 years of experience in Software Engineering DevOps MLOps or Platform Engineering.
Strong understanding of:
oLLM-based coding tools or AI copilots
oCI/CD pipelines
oCloud platforms (AWS Azure GCP)
oContainerization (Docker Kubernetes)
Hands-on experience integrating or configuring developer platforms.
Familiarity with secure coding enterprise security standards and governance systems.
Strong scripting knowledge (Python Bash YAML).
Excellent communication and stakeholder management skills.
Preferred Qualifications
Experience implementing AI agents or autonomous coding tools.
Exposure to GitHub Copilot AWS CodeWhisperer or similar tools.
Understanding of SDLC automation IaC (Terraform) and DevSecOps practices.
Prior experience working with enterprise engineering transformation projects.
Certifications in cloud (AWS/Azure/GCP) DevOps or AI tools.