# Senior Engineer, AI Engineering (R5459)

**Company**: Shield AI
**Work arrangement**: onsite
**Experience**: senior
**Job type**: full-time
**Salary**: USD 160,000-290,000 per-year-salary
**Category**: Engineering
**Industry**: Technology

**Apply**: https://jobs.lever.co/shieldai/a32a2559-8aa2-4d18-ae61-41cbfbfb644a?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply
**Canonical**: https://yubhub.co/jobs/job_0c4749da-f09

## Description

The Senior Engineer, AI Engineering is a hands-on individual contributor responsible for building and operating AI-enabled solutions, reusable components, integrations, automations, and measurement capabilities that accelerate enterprise AI adoption.

**AI Solution Delivery & Productivity Enablement**

- Build AI-assisted tools, workflow automations, agents, prompts, and integrations that reduce manual effort and improve individual and team productivity.

- Partner with business stakeholders to understand high-friction workflows, translate them into technical requirements, and deliver fit-for-purpose AI solutions.

- Implement AI-augmented collaboration patterns such as meeting intelligence, document generation, contextual knowledge retrieval, task automation, and internal assistant workflows.

- Develop and maintain internal enablement assets including prompt templates, agent examples, skill templates, playbooks, and usage guidance.

- Collect user feedback and operational telemetry to improve adoption, usability, reliability, and measured impact.

**Reusable Components & Integrations**

- Build and maintain reusable AI components including connectors, integration adapters, prompt modules, data pipelines, skill templates, and service wrappers.

- Contribute to shared component libraries using established quality, documentation, versioning, testing, and deprecation practices.

- Integrate AI capabilities with enterprise systems, collaboration tools, knowledge repositories, data platforms, and workflow automation platforms.

- Create developer-facing documentation, examples, and onboarding material that help other teams adopt shared AI components safely and efficiently.

- Identify repeatable patterns from project work and convert them into reusable assets for broader enterprise use.

**Responsible AI Controls & Operations**

- Implement engineering controls for data handling, access management, prompt safety, output validation, audit logging, and secure integration patterns.

- Follow enterprise AI architecture and governance standards while escalating gaps, risks, or implementation challenges to technical leads.

- Build or maintain dashboards for AI usage, adoption, policy adherence, cost visibility, error patterns, and operational health.

- Support model, prompt, and agent lifecycle activities such as evaluation, version tracking, testing, rollout, monitoring, and rollback.

- Participate in security, privacy, and governance reviews by providing implementation details, evidence, and remediation support.

**Cost, ROI & Cross-Functional Execution**

- Instrument AI solutions to capture usage, performance, cost, quality, and productivity metrics.

- Support cost optimization work through usage analysis, model efficiency improvements, license rationalization inputs, and service tuning.

- Help connect AI solution usage to measurable outcomes such as time savings, error reduction, throughput improvement, and capacity creation.

- Collaborate with Engineering, IT, Security, Legal, Data, Finance, and business unit teams to deliver reliable AI capabilities in a matrixed environment.

- Contribute to AI communities of practice by sharing lessons learned, reusable patterns, demos, and implementation guidance.

## Skills

### Required
- enterprise software
- automation
- data
- AI
- digital workplace solutions
- large language models
- generative AI tools
- APIs
- RAG systems
- agents
- prompt workflows
- AI-assisted automation
- API design
- testing
- observability
- documentation
- secure coding practices
- maintainable implementation patterns
- integrations with enterprise systems
- collaboration platforms
- knowledge repositories
- data platforms
- workflow automation tools
- AI governance concepts
- access controls
- data classification
- audit logging
- prompt safety
- output validation
- model/prompt versioning
- instrumenting systems with telemetry
- logging
- dashboards
- usage metrics
- cost/performance monitoring

### Nice to have
- regulated environments
- security-sensitive environments
- defense-adjacent environments
- data-governed environments
- enterprise AI tooling ecosystems
- copilot platforms
- workflow automation suites
- RAG platforms
- vector databases
- enterprise search
- MLOps
- model evaluation
- AI observability
- prompt/agent testing
- production monitoring
- Databricks
- Snowflake
- lakehouse architectures
- usage dashboards
- cost reporting
- showback inputs
- ROI measurement
- reusable component libraries
- internal developer platforms
- templates
- enablement playbooks

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Source: [Apply at jobs.lever.co](https://jobs.lever.co/shieldai/a32a2559-8aa2-4d18-ae61-41cbfbfb644a?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply)