Domain Specialist – Maintenance, Reliability & Inspection (Oil & Gas)

Infosys•Houston, TX

About The Position

Infosys is seeking a hands-on Oil & Gas domain specialist in maintenance, reliability, operations, and inspection who can connect operational expertise with data, engineering, and AI delivery. The specialist will translate field and engineering challenges into deployable solutions, guide multidisciplinary teams from discovery through adoption, and build the client-facing and technical capabilities needed to progress into a Forward Deployed Engineer role within 2–3 years. The role serves as a domain authority across upstream, midstream, or downstream operations. It involves engaging client stakeholders, mapping operational workflows, translating domain needs into solution requirements, and partnering with product, data, AI, and software engineering teams to prototype, deploy, validate, and improve solutions in client environments. The specialist also supports data readiness, testing, rollout, training, adoption, troubleshooting, and measurement of business outcomes. The position requires 8–10 years of relevant Oil & Gas experience, strong knowledge of maintenance and reliability practices, and the ability to evaluate analytical and AI outputs for operational relevance, explainability, safety, and engineering validity. A bachelor’s degree in a relevant engineering discipline is required. Infosys is unable to provide immigration sponsorship for this role; applicants must be authorized to work in the United States without employer-based visa sponsorship.

Requirements

8–10 years of experience in maintenance, reliability, asset integrity, or inspection within the Oil & Gas industry.
Strong knowledge of root cause analysis, FMEA, RCM, condition monitoring, risk-based inspection, defect management, and maintenance work processes.
Practical understanding of rotating or fixed equipment, degradation and failure mechanisms, operating envelopes, and key reliability and integrity indicators.
Working knowledge of equipment sensor and time-series data, inspection records, work orders, failure history, engineering documents, and master data.
Ability to assess the operational relevance of physics-based, statistical, and machine-learning models and challenge outputs constructively.
Awareness of modern AI capabilities, including predictive analytics, anomaly detection, knowledge graphs, generative AI, and workflow automation.
Ability to conduct credible technical conversations with client SMEs and communicate clearly with technical and non-technical stakeholders.
Proven experience leading workshops, resolving ambiguity, making practical trade-offs, and guiding decisions to clear outcomes.
Strong problem-solving, structured thinking, written communication, and executive presentation skills.
Comfort working in multidisciplinary, fast-paced teams with changing priorities and direct accountability for outcomes.
Experience with enterprise asset management and maintenance systems such as SAP PM, IBM Maximo, or equivalent platforms.
Exposure to historians, analytics platforms, data products, dashboards, cloud services, APIs, SQL, Python, or low-code tools.
Experience delivering digital transformation, AI, asset performance management, or connected-worker solutions in an asset-intensive industry.
Familiarity with Agile delivery, product management, DevOps/MLOps concepts, cybersecurity, data governance, and production support.
Bachelor’s degree in mechanical, chemical, petroleum, industrial, or a related engineering discipline.
Candidates must be authorized to work for any employer in the United States without employer-based visa sponsorship; Infosys cannot provide immigration sponsorship for this role.

Nice To Haves

A master’s degree.
Relevant professional certification.
Certifications in reliability, inspection, maintenance management, data, cloud, or AI.

Responsibilities

Serve as the domain authority for maintenance, reliability, and inspection processes across upstream, midstream, or downstream operations.
Map end-to-end workflows from anomaly detection through root cause analysis, decision-making, and corrective or preventive action.
Engage client SMEs, engineers, operators, and business leaders to understand operational challenges, clarify priorities, and validate solution approaches.
Plan and facilitate discovery, design, and validation workshops to uncover requirements, pain points, constraints, and value opportunities.
Translate domain needs into use cases, user stories, data requirements, business rules, acceptance criteria, and solution designs for data and engineering teams.
Identify opportunities for AI, analytics, and automation to accelerate root cause analysis, predict failures, recommend actions, and improve maintenance execution.
Evaluate data-driven and physics-based model outputs for operational relevance, explainability, safety, and engineering validity.
Partner with product, data, AI, and software engineering teams to prototype, test, deploy, and continuously improve solutions in client environments.
Support data readiness assessments, solution validation, user acceptance testing, rollout, training, and end-user adoption.
Define success measures and track outcomes such as reduced downtime, improved reliability, faster investigation, inspection efficiency, and avoided cost.
Troubleshoot functional, data, workflow, and adoption issues during pilots and production deployment, coordinating resolution across client and technical teams.
Document decisions, reusable patterns, lessons learned, and domain assets; contribute to proposals, demonstrations, and solution discussions.