Platform Engineer- AI

About the Role

Smarsh is seeking an experienced Senior Software Engineer to design and build the next generation of Agentic Modules — the atomic, specification-driven building blocks of the Smarsh Agentic Development Lifecycle (AI-SDLC).

Agentic Modules are AI-ready, self-contained bundles that encapsulate specifications, code, infrastructure, telemetry, and policy context to deliver product outcomes safely, predictably, and autonomously. Each module begins with a spec-driven contract — defining intent, inputs, expected outcomes, and governance rules — serving as the single source of truth between human developers, AI agents, and the Fabric platform.

You will play a pivotal role in defining how these executable specifications evolve from design artifacts into operational software, enabling a new model of collaborative product development where AI and humans co-create, validate, and ship features through structured automation.

This role sits at the intersection of AI enablement, platform engineering, and product development automation — shaping how Smarsh designs, builds, and governs software in an intelligent, spec-first engineering ecosystem.

What You Bring

Engineering Depth

5+ years of experience in software engineering, platform engineering, or DevOps automation.

Strong programming skills in Python, Go, or TypeScript, with a focus on reusable frameworks and automation systems.

Proficiency with Kubernetes, Terraform, and CI/CD systems such as Argo, GitHub Actions, or GitLab CI.

Experience with policy-as-code (OPA) and compliance automation pipelines.

Understanding of software supply chain security, auditability, and change governance in complex ecosystems.

AI & Platform Awareness

Familiarity with AI-assisted developer workflows, copilot systems, or agent orchestration frameworks.

Experience designing systems that combine human intent with AI execution, using structured specifications as the interface.

Understanding of AI context propagation, prompt scaffolding, and autonomous reasoning in software workflows.

Knowledge of telemetry pipelines, Open Telemetry, and feedback loops between automation and insight.

Architectural & System Thinking

Proven ability to design modular, extensible systems that enable spec-to-execution automation.

Deep understanding of SDLC and AI-DLC convergence, including traceability, auditability, and compliance design patterns.

Strong grasp of platform architecture, composable frameworks, and integration across CI/CD, IaC, and AI systems.

Capable of thinking across data, process, and automation layers to create cohesive, scalable patterns.

Collaboration & Communication

Exceptional ability to collaborate across disciplines — AI, platform, product, and compliance.

Clear technical communicator with a product mindset — able to bridge specification detail with outcome focus.

Systems thinker who can articulate and evangelize spec-first engineering as the foundation for intelligent automation.

Preferred Qualifications

Prior experience in DevSecOps, platform enablement, or engineering systems architecture.

Exposure to AI agent frameworks, LLM integration, or autonomous software delivery systems.

Experience building self-service developer platforms and specification-driven automation systems.

Familiarity with AI governance, policy observability, and AI validation frameworks.

Contributions to open-source automation, observability, or AI orchestration projects.

What You'll Do

Build the Agentic CI/CD Module Platform

Design and implement the Agentic Module architecture, enabling engineers and AI agents to define, execute, and audit engineering workflows as modular, spec-driven units.

Build specification-driven pipelines that transform module specs into validated, executable artifacts — including build logic, policy enforcement, and telemetry binding.

Develop reusable Agentic Module SDKs and templates for CI/CD, testing, refactoring, and compliance workflows.

Ensure every module includes machine-readable specifications that define scope, dependencies, success criteria, and AI guidance.

Contribute to the design of spec-to-execution frameworks that translate intent into code, infrastructure, and policy actions within the Smarsh Fabric.

Embed Policy, Compliance, and Observability

Integrate policy-as-code and governance hooks that enforce compliance and approvals directly from the specification layer.

Implement telemetry emitters that provide full lifecycle visibility across build, deploy, and run stages of each Agentic Module.

Define the observability schema that allows modules to self-report status, DORA metrics, ROI analytics, and AI participation telemetry.

Ensure all execution is auditable, reversible, and explainable, supporting traceability across human and AI-driven actions.

Engineer for AI Enablement and AI-DLC Integration

Collaborate with AI platform teams to make Agentic Modules AI-executable — enabling agents to consume specifications, perform reasoning, and trigger compliant execution flows.

Implement metadata and orchestration patterns that make specifications machine-interpretable and policy-aware.

Design feedback loops where AI agents validate, improve, and extend specifications over time, accelerating the AI-DLC.

Prototype spec evolution mechanisms where specifications adapt based on telemetry, performance data, and policy insights.

Contribute to Platform Architecture

Partner with Platform Engineering to embed Agentic Module orchestration into the Fabric runtime and AI-DLC pipelines.

Develop integrations between the specification framework, CI/CD systems, IaC repositories, and AI validation engines.

Influence architectural decisions to ensure every change — whether human or AI-initiated — flows through specification-driven governance and observability.

Define patterns that make AI participation safe, explainable, and policy-bound across all stages of product delivery.

Developer Experience & Enablement

Build intuitive tooling for engineers to author, validate, and execute Agentic Module specifications.

Deliver documentation, examples, and SDKs that empower developers to adopt spec-first, AI-assisted delivery patterns.

Champion the developer experience — making the AI-DLC frictionless, observable, and auditable by design.

Lead workshops, internal communities, and enablement efforts to drive adoption across Smarsh engineering teams.