Senior Engineer, AI Engineering (R5459) at Shield AI | United States | Rezi

Senior Engineer, AI Engineering (R5459) at Shield AI

Senior Engineer, AI Engineering (R5459)

Shield AI · United States

5 days ago

Senior Engineer, AI Engineering (R5459)

Shield AI · United States

5 days ago
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About the Role

Shield AI is seeking a Senior Engineer, AI Engineering to build and operate AI-enabled solutions, reusable components, integrations, automations, and measurement capabilities that accelerate enterprise AI adoption. This role will convert high-friction workflows into secure, reliable, measurable AI capabilities, delivering production-quality agents, prompts, connectors, dashboards, and workflow automations while adhering to established standards.

Responsibilities

  • 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.
  • 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.
  • 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.
  • 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.

Requirements

  • Progressive experience building enterprise software, automation, data, AI, or digital workplace solutions.
  • Hands-on experience integrating large language models, generative AI tools, APIs, RAG systems, agents, prompt workflows, or AI-assisted automation into production or enterprise environments.
  • Strong software engineering fundamentals including API design, testing, observability, documentation, secure coding practices, and maintainable implementation patterns.
  • Experience building integrations with enterprise systems, collaboration platforms, knowledge repositories, data platforms, or workflow automation tools.
  • Working knowledge of AI governance concepts such as access controls, data classification, audit logging, prompt safety, output validation, and model/prompt versioning.
  • Ability to convert ambiguous business workflows into practical technical solutions in partnership with stakeholders.
  • Experience instrumenting systems with telemetry, logging, dashboards, usage metrics, or cost/performance monitoring.
  • Clear communication skills and a collaborative style suitable for working across business, engineering, security, legal, and data teams.

Skills

  • AI Solution Delivery
  • Productivity Enablement
  • AI-augmented collaboration
  • Reusable Components
  • Integrations
  • Responsible AI Controls
  • Operations
  • Cost Optimization
  • ROI Measurement
  • Cross-Functional Execution
  • Large language models
  • Generative AI tools
  • APIs
  • RAG systems
  • Agents
  • Prompt workflows
  • API design
  • Testing
  • Observability
  • Documentation
  • Secure coding practices
  • Enterprise systems integration
  • Collaboration platforms integration
  • Knowledge repositories integration
  • Data platforms integration
  • Workflow automation tools integration
  • AI governance
  • Telemetry
  • Logging
  • Dashboards
  • Usage metrics
  • Cost/performance monitoring
  • MLOps
  • Model evaluation
  • AI observability
  • Prompt/agent testing
  • Production monitoring
  • Data platforms
  • Databricks
  • Snowflake
  • Lakehouse architectures
  • Enterprise search
  • Copilot platforms
  • Workflow automation suites
  • RAG platforms
  • Vector databases

Location

  • U.S.
  • Europe
  • Middle East
  • Asia-Pacific

Work Type

  • Full-time

Experience Level

  • Senior

Education Level

  • Degree in Computer Science, Engineering, Data Science, or a related technical field, or equivalent practical experience.

Salary/Compensations

  • $160,000 - $290,000 a year

Benefits

  • Bonus
  • Benefits
  • Equity
  • Temporary benefits package (applicable after 60 days of employment)

About the Company

  • Founded in 2015, Shield AI is a venture-backed defense-tech company with the mission of protecting service members and civilians with intelligent systems.
  • Its products include Hivemind autonomy software and V-BAT and X-BAT aircraft.
  • With offices and facilities across the U.S., Europe, the Middle East, and Asia-Pacific, Shield AI’s technology actively supports operations worldwide.
  • For more information, visit www.shield.ai.
  • Follow Shield AI on LinkedIn, X, Instagram, and YouTube.

Equal Opportunity

  • Shield AI is proud to be an equal opportunity workplace and is an affirmative action employer.
  • We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, marital status, disability, gender identity or Veteran status.
  • If you have a disability or special need that requires accommodation, please let us know.