Key Responsibilities

Automation Development & Engineering

• Design, develop, test, and maintain automation solutions, integrations, workflows, and reusable engineering components
• Build solutions that improve software delivery, testing, documentation, operational processes, and employee productivity
• Translate business and technical requirements into scalable automation using APIs, scripting languages, cloud services, and workflow platforms
• Develop reusable templates, connectors, scripts, prompts, and implementation patterns that can be leveraged across multiple teams
• Support proof-of-concept initiatives and help mature successful solutions into production-ready capabilities
• Continuously identify opportunities to reduce manual effort through automation and intelligent workflows

AI-Enabled Productivity & Engineering

• Develop AI-assisted workflows that enhance:
  • Software development
  • Testing and quality assurance
  • Documentation generation
  • Code review processes
  • Knowledge management
  • Technical research and analysis
• Configure and support enterprise AI productivity tools and digital assistants
• Build automation for:
  • Document processing
  • Summarization
  • Classification
  • Workflow routing
  • Ticket analysis
  • Knowledge retrieval
  • Meeting and collaboration support
• Partner with engineering and operations teams to identify repetitive processes suitable for automation
• Create documentation, best practices, and enablement materials that support responsible AI adoption

Integration & Platform Development

• Build integrations between AI solutions and enterprise applications, APIs, databases, collaboration tools, cloud services, and workflow platforms
• Support the development of AI-powered solutions using modern technologies such as:
  • Large language models
  • Knowledge retrieval systems
  • Semantic search
  • Intelligent document processing
  • AI orchestration frameworks
• Develop reusable services and components for prompt management, response validation, logging, monitoring, and operational support
• Contribute to scalable platform capabilities that enable broader adoption of AI-powered solutions across the organization

Operations & Process Automation

• Develop automation that improves:
  • Monitoring and observability
  • Incident management
  • Operational workflows
  • Service delivery
  • Knowledge management
  • Support processes
• Partner with infrastructure and operations teams to streamline workflows through automation and intelligent tooling
• Integrate automation solutions with monitoring, ticketing, collaboration, and service management platforms
• Create operational documentation, runbooks, and support materials for implemented solutions
• Track and measure improvements in efficiency, cycle time reduction, productivity, and operational effectiveness

Security, Quality & Reliability

• Apply secure development practices throughout the design and implementation process
• Ensure automation solutions meet organizational standards for security, privacy, access controls, and operational reliability
• Collaborate with architecture, security, data, and governance stakeholders to ensure solutions are scalable, supportable, and compliant
• Perform testing, validation, and performance tuning of automation solutions
• Identify risks, dependencies, and operational requirements early in the delivery lifecycle
• Contribute to monitoring, observability, and continuous improvement practices

Collaboration & Continuous Improvement

• Work closely with engineers, architects, product teams, business stakeholders, and external partners to deliver high-impact automation initiatives
• Participate in design reviews, code reviews, testing, troubleshooting, and implementation planning
• Document solutions, configurations, reusable patterns, operational procedures, and lessons learned
• Contribute to engineering standards, best practices, technical playbooks, and knowledge-sharing initiatives
• Continuously improve solution quality, reliability, maintainability, security, and reusability

Qualifications

Experience

• 4+ years of experience in software engineering, automation, integration development, cloud technologies, platform engineering, IT operations, or related technical disciplines
• 2+ years of experience working with AI, machine learning, automation platforms, advanced analytics, developer productivity tools, or emerging technologies
• Demonstrated experience building automation solutions, integrations, workflow applications, or reusable engineering components
• Experience supporting enterprise technology environments preferred

Technical Skills

• Hands-on experience with:
  • APIs and integrations
  • Workflow automation platforms
  • Cloud services
  • Scripting and software development
  • Modern engineering and productivity tools
• Experience with one or more programming languages such as:
  • Python
  • JavaScript / TypeScript
  • PowerShell
  • Bash
  • Java
  • C# / .NET
• Familiarity with:
  • Generative AI concepts and applications
  • Large language models and AI assistants
  • Retrieval and search-based AI architectures
  • Prompt engineering and evaluation techniques
  • AI workflow orchestration and automation patterns
• Working knowledge of:
  • CI/CD pipelines
  • DevSecOps practices
  • Test automation
  • Monitoring and observability
  • Identity and access management
  • Security and privacy principles

Preferred Qualifications

• Experience with enterprise AI platforms and productivity tools
• Experience building intelligent automation or AI-powered workflow solutions
• Exposure to regulated environments with strong security, privacy, or compliance requirements
• Experience supporting operational automation, developer productivity, or IT service management initiatives

Education

• Bachelor's degree in Computer Science, Engineering, Information Systems, Data Science, or a related field preferred
• Equivalent practical experience will be considered