Job Title

Overview Tata Consultancy Services (TCS) is an equal opportunity employer, and embraces diversity in race, nationality, ethnicity, gender, age, physical ability, neurodiversity, and sexual orientation, to create a workforce that reflects the societies we operate in. Our continued commitment to Culture and Diversity is reflected in our people stories across our workforce and implemented through equitable workplace policies and processes. About TCS: TCS is an IT services, consulting, and business solutions organization that has been partnering with many of the worlds largest businesses in their transformation journeys for over 55 years. Its consulting-led, cognitive-powered portfolio of business, technology, and engineering services and solutions is delivered through its unique Location Independent Agile delivery model, recognized as a benchmark of excellence in software development. A part of the Tata group, India''''s largest multinational business group, TCS operates in 55 countries and employs over 607,000 highly skilled individuals, including more than 10,000 in Canada. The company generated consolidated revenues of US $ 30 billion in the fiscal year ended March 31, 2025 and is listed on the BSE and the NSE in India. TCS'''' proactive stance on climate change and award-winning work with communities across the world have earned it a place in leading sustainability indices such as the MSCI Global Sustainability Index and the FTSE4Good Emerging Index. Qualifications Skill Required: Professional software engineering, including building and shipping GenAI or LLM-driven products. Architect, develop, and deploy GenAI services that ingest SCADA, PI System, WITSML, and reservoir data to deliver insights for drilling optimization, equipment reliability, and emissions reduction. Fine-tune and evaluate large language and vision models on domain-specific corpora (well files, P&IDs, procedures, regulatory filings). Build secure, scalable APIs and micro-services in Python/TypeScript; containerize with Docker and serve on Kubernetes/EKS or OpenShift. Implement retrieval-augmented generation pipelines with vector databases (e.g., OpenSearch, Milvus) to enable fast technical-document Q&A for engineers and field operators. Optimize model inference on GPUs/accelerators using DeepSpeed, TensorRT, or vLLM; benchmark latency, throughput, and cost. Embed GenAI capabilities into web, mobile, and edge applications used at well sites, plants, and control centres, ensuring robust observability and rollback. Uphold best-practice software engineering: CI/CD (GitHub Actions, ArgoCD), automated testing, IaC (Terraform/Pulumi), and secure coding aligned with AER regulatory requirements. Monitor academic and industry advances (RLHF, RAG, agentic workflows) and champion pragmatic adoption in oil & gas contexts. Design and implement data pipelines and analytics frameworks for large-scale structured/unstructured data. Define data governance and quality standards for analytics and AI models. Integrate GenAI with BI dashboards and predictive analytics workflows. Ensure data security and compliance across analytics and AI systems. Good communication, analytical, presentation and documentation skills. Good to have skills: Experience integrating GenAI with historian data, geoscience interpretation tools (Petrel, Kingdom), or maintenance systems (SAP PM, Maximo). Contributions to open-source GenAI/ML projects or published papers. Familiarity with LangChain, LlamaIndex, or similar orchestration frameworks. Knowledge of energy-sector regulations (AER, CAPP) impacting data use and model governance. Background in real-time analytics for production optimization or flare/emissions monitoring. Experience with data visualization tools (Power BI, Tableau). Knowledge of data warehousing and lakehouse architectures. Familiarity with ETL tools and data orchestration frameworks (Airflow, dbt). Responsibilities Design and development: Create automated systems, frameworks, and scripts for machinery or software applications. This includes designing the system architecture and developing solutions for automation problems. Implementation and integration: Deploy automation solutions and integrate them with existing systems and other tools. This can involve working with tools like Ansible, Kibana, or CI/CD pipelines. Maintenance and troubleshooting: Troubleshoot and resolve automation errors and bugs. They are also responsible for maintaining and upgrading existing automation technology and improving system performance. Collaboration and communication: Work with cross-functional teams, such as developers and QA professionals, to identify automation opportunities and define requirements. They also provide technical support and training to colleagues. Testing and quality assurance: Develop test automation frameworks and scripts to validate product functionality and performance. They analyze test results, report defects, and ensure the quality of the automated systems. Define data architecture strategy for analytics and AI integration Build data pipelines and analytics dashboards for operational insights Collaborate with business teams to translate analytics needs into AI-driven solutions. Thank you for your interest in TCS. Candidates that meet the qualifications for this position will be contacted within a 2-week period. We invite you to continue to apply for other opportunities that match your profile. #J-18808-Ljbffr