[Remote] AI Automation Engineer 0626
Note: The job is a remote job and is open to candidates in USA. Nexus IT Group is seeking an AI Automation Engineer to design, develop, and maintain automation solutions that enhance software delivery and employee productivity. The role involves building integrations between AI solutions and enterprise applications, as well as developing AI-assisted workflows to streamline various processes.
Responsibilities
- 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
- 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
- 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
- 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
- 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
- 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
Skills
- 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
- Hands-on experience with APIs and integrations
- Hands-on experience with workflow automation platforms
- Hands-on experience with cloud services
- Hands-on experience with scripting and software development
- Hands-on experience with 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
- Familiarity with large language models and AI assistants
- Familiarity with retrieval and search-based AI architectures
- Familiarity with prompt engineering and evaluation techniques
- Familiarity with AI workflow orchestration and automation patterns
- Working knowledge of CI/CD pipelines
- Working knowledge of DevSecOps practices
- Working knowledge of test automation
- Working knowledge of monitoring and observability
- Working knowledge of identity and access management
- Working knowledge of security and privacy principles
- 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
- Bachelor's degree in Computer Science, Engineering, Information Systems, Data Science, or a related field preferred
- Equivalent practical experience will be considered
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