AVEVA PI Engineer

Job Title: AVEVA PI Engineer Hiring FAST!
Industry: Utility
Location: Charlotte, NC
Pay Rate: $85-95/HR on W2 Only NO C2C
Setting: Remote
Duration: 24 months
Job ID: 245636

Required Qualifications:

• 7+ years of professional software development experience, including leading delivery for other developers or squads.
• Automation
• Cloud
• GenAI
• AVEVA PI Ecosystem
• AWS
• Strong AWS experience building production-grade services and automation workflows.
• Demonstrated ability to lead execution across multiple simultaneous initiatives: scoping, planning, dependency management, and delivery.
• Experience working in Agile/Scrum environments using JIRA (technical contribution to planning/refinement; collaboration with delivery roles).
• Hands-on experience with Infrastructure-as-Code for cloud environments (Terraform preferred; CloudFormation familiarity a plus).
• Strong SDLC discipline: Git-based workflows, CI/CD practices, code review, documentation, and operational readiness.
• Excellent communication skills: ability to translate between business needs and technical implementation plans.

Desired Qualifications:

• Experience in the AVEVA/OSIsoft PI ecosystem (Data Archive, Asset Framework, PI Vision, PI Web API/SDKs) or similar industrial/historian platforms.
• Experience modernizing legacy applications into enterprise architecture standards (security, supportability, observability, and documentation).
• Hands-on experience with .NET/C#, SQL, PowerShell, and at least one modern scripting/runtime language (e.g., Python, Node.js).
• Experience with monitoring/log aggregation and operational tooling (e.g., CloudWatch, Splunk, Elastic, Dynatrace).
• Applied experience delivering GenAI prototypes or internal productivity/automation solutions.

Responsibilities:

• Own day-to-day technical execution across multiple parallel workstreams: clarify scope, define next steps, and drive delivery to completion.
• Break down ambiguous requirements into actionable epics/stories/tasks; identify dependencies, risks, and sequencing.
• Guide and mentor developers: propose implementation approaches, teach patterns/standards, and delegate work appropriately.
• Ensure delivery outputs are enterprise-ready: maintainability, security controls, operational readiness, and documentation/runbooks.
• Partner with architecture/standards owners to ensure implementation aligns to published design principles and coding standards.
• Provide clear status updates to technical and non-technical stakeholders; escalate risks and blockers early.
• Collaborate closely with the team s Project Manager and Agilist who coordinate Agile ceremonies, reporting, and cadence.
• Bring technical context to sprint planning and backlog refinement: help ensure stories are implementable, risks/dependencies are understood, and acceptance criteria are clear.
• Support delivery execution during the sprint by helping engineers stay aligned on scope, sequencing, and next steps in JIRA.
• Design, build, and enhance AWS-based automation workflows and services (commonly including Step Functions, Lambda,
• Systems Manager (SSM), S3, DynamoDB, IAM/RBAC, and related services).
• Build and maintain cloud infrastructure using Infrastructure-as-Code (Terraform preferred; CloudFormation familiarity a plus).
• Implement reliability engineering practices: observability, log/metric/trace instrumentation, failure handling, retries, runbooks, and root-cause analysis.
• Support secure-by-design implementations: least-privilege access patterns, credential governance, and auditability.
• Leverage enterprise secrets and privileged access tooling as appropriate (e.g., HashiCorp Vault, CyberArk, BeyondTrust).
• Participate in and/or lead code reviews; enforce engineering standards and best practices.
• Create or improve technical documentation: architecture notes, designs, SOPs, runbooks, deployment/backout plans, and support procedures.
• Drive testing discipline (unit/integration) and support production deployment readiness activities.
• Lead or support delivery of GenAI proof-of-concepts in collaboration with an internal AI community of practice, with a focus on outcomes that can scale in subsequent phases.
• Work with product and stakeholders to define success criteria, technical approach, and roadmap for expansion.