AI Architect (Forward Deployed Engineer)

We are seeking an experienced AI-SDLC Architect (FDE) to help enterprise engineering teams transform traditional software development lifecycles into AI-native, agentic development workflows. The ideal candidate will combine expertise in AI-powered software engineering, platform architecture, CI/CD, and stakeholder engagement to drive AI-assisted development at scale.

Key Responsibilities

Architect and implement AI-native SDLC workflows, from specification-driven development through deployment.

Design and deploy AI coding agent architectures integrated with enterprise development pipelines and cloud platforms.

Define reference architectures, blueprints, and governance models for AI-assisted software delivery.

Build scalable, secure CI/CD pipelines incorporating AI tooling, security controls, and quality gates.

Collaborate directly with client engineering teams to drive adoption of agentic development practices.

Provide technical leadership, design reviews, and best practices for AI-enabled software engineering.

Mandatory Requirements

12-15 years of experience in software engineering, architecture, or platform engineering.

Hands-on experience with AI development tools such as GitHub Copilot, Copilot CLI, Claude Code, VS Code AI extensions, or equivalent.

Experience implementing spec-driven development using SpecKit, OpenSpec, BMD, or similar frameworks.

Strong understanding of AI artifact management, FinOps/token consumption management, and AI guardrails.

Experience designing agent memory management (static, dynamic, and episodic memory) and multi-agent orchestration.

Proven expertise in architecting AI-native software delivery platforms and developer workflows for enterprise environments.

Strong knowledge of FastAPI (or equivalent API frameworks).

Experience with Azure OpenAI, Amazon Bedrock, or similar AI gateway architectures.

Expertise in Infrastructure as Code (Terraform) and CI/CD pipelines using GitHub Actions or equivalent tools.

Preferred Skills

• Experience as a Forward Deployed Engineer, Solution Architect, or Lead Engineer working directly with client teams.
• Strong Python development background.
• Experience with AI security, evaluation frameworks, observability, and monitoring.
• Knowledge of Docker, Kubernetes, cloud-native deployments, and enterprise security practices.
• Exposure to both AWS and Azure environments.