Inclusion without Exception
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.
Tata Consultancy Services (BSE: 532540, NSE: TCS) is the technology partner of choice for industry-leading organizations worldwide. Since its inception in 1968, TCS has upheld the highest standards of innovation, engineering excellence and customer service.
It has set an aspiration to become the world's largest AI-led technology services company and is enabling its clients to transform themselves across the full AI stack, from infrastructure to intelligence.
Rooted in the heritage of the Tata Group, TCS is focused on creating long term value for its clients, its investors, its employees, and the community at large. With a highly skilled workforce spread across 56 countries and 194 service delivery centers across the world, the company has been recognized as a top employer in six continents. With the ability to rapidly apply and scale new technologies, the company has built long term partnerships with its clients. Many of these relationships have endured into decades and navigated every technology cycle, from mainframes in the 1970s to artificial intelligence today.
Must-Have Technical / Functional Skills
- Demonstrated experience in Data Engineering, AI Application Development, Cloud Data Platforms, and Production-grade Software Engineering, with a proven track record of delivering enterprise-scale solutions.
- Strong hands-on expertise in Python, PySpark, SQL, REST APIs, Fast API, and enterprise application integration.
- Experience designing and building AI-powered applications using Claude, Prompt Engineering, Retrieval-Augmented Generation (RAG), Vector Databases, Semantic Search, and Agentic AI patterns.
- Deep understanding of Data Engineering frameworks, including ETL/ELT, batch and streaming pipelines, data quality, metadata management, lineage, observability, and Data Ops practices.
- Experience implementing and operationalizing MLOps/LLMOps capabilities, including model lifecycle management, CI/CD pipelines, MLflow, monitoring, deployment automation, rollback, and production support.
- Strong knowledge of cloud and modern data platforms, including compute, storage, integration, orchestration, security, networking, monitoring, and cost optimization services.
- Hands-on experience with Git, Docker, Kubernetes, Airflow, MLflow, CI/CD, and distributed data processing frameworks.
- Strong understanding of enterprise security and governance principles, including IAM/RBAC, encryption, secrets management, privacy controls, auditability, compliance, and secure data access.
- Ability to translate business requirements into scalable solution designs, define non-functional requirements, estimate effort, and drive production-ready implementation.
- Experience working with Banking, Financial Services, or Insurance (BFSI) data environments and familiarity with regulatory, security, privacy, and resilience requirements.
- Strong client-facing consulting skills with experience conducting discovery workshops, solution shaping, rapid prototyping, stakeholder communication, and technical presentations.
- Bachelor’s degree in Computer Science, Engineering, Information Systems, Data Management, or a related discipline.
- Preferred certifications in Cloud Platforms, Kubernetes, AI Engineering, MLOps, Data Engineering, Enterprise Architecture, Security, or Program Delivery.
- Experience working in a forward-deployed delivery model by embedding with subject matter experts, business users, and engineering teams through solution validation, production deployment, adoption, and handover.
- Strong hands-on data discovery skills, including profiling unfamiliar data with Python, pandas, PySpark, and SQL; assessing coverage and quality; and quantifying volumes, distributions, edge cases, and business-process gaps before development.
- Ability to rapidly build thin working solutions using real data and APIs, validate them with users, and iteratively harden them with automated tests, security controls, error handling, observability, and production support procedures.
- Experience creating business-relevant evaluation datasets with subject matter experts, measuring ML or LLM quality, performing structured error analysis, grouping failures by root cause, and prioritizing improvements across releases.
- Demonstrated production ownership after go-live, including monitoring, incident diagnosis, rollback, stabilization, performance and latency troubleshooting, and resolution of user-reported issues.
- Ability to measure user adoption and business impact after launch using usage data and agreed KPIs such as time saved, error reduction, straight-through processing, quality improvement, or productivity gains.
- Willingness and ability to travel or work onsite with stakeholders when an engagement requires close collaboration and accelerated delivery.
Roles & Responsibilities
- Design, develop, and deploy enterprise-grade AI and data applications using Python, PySpark, Claude, SQL, APIs, and modern cloud-based data platforms.
- Engage with business and technology stakeholders to understand business objectives, data landscapes, functional requirements, non-functional requirements, and delivery expectations.
- Define solution architecture, implementation roadmaps, and technical approaches that align with business goals and operational requirements.
- Architect scalable data platforms, data pipelines, and AI solutions with a strong focus on performance, security, reliability, and cost optimization.
- Develop batch, real-time, and streaming data processing solutions integrating multiple enterprise data sources and downstream applications.
- Build and operationalize Claude-powered applications, copilots, and AI workflows using prompt engineering, Retrieval-Augmented Generation (RAG), vector search, and enterprise data integration.
- Implement responsible AI practices, including governance, security, privacy, traceability, validation, and human oversight controls.
- Design and enforce engineering standards, reusable frameworks, CI/CD practices, infrastructure automation, and production deployment patterns.
- Provide technical leadership across solution design, code reviews, architecture reviews, testing, deployment, and production support activities.
- Drive platform reliability, performance tuning, observability, incident resolution, and operational excellence across data and AI workloads.
- Collaborate closely with architects, data engineers, AI specialists, platform teams, and stakeholders to deliver production-ready solutions.
- Support solutioning, RFP responses, technical demonstrations, effort estimation, and workshops for new opportunities.
- Develop reusable accelerators, reference architectures, implementation playbooks, and engineering best practices to improve delivery efficiency.
- Mentor engineering teams and contribute to hiring, capability development, technical assessments, and knowledge-sharing initiatives.
- Embed with subject matter experts, product owners, and engineers for defined outcomes; map workflows, users, data, constraints, and decision points; and establish measurable success criteria.
- Analyze data early to assess coverage, quality, volumes, distributions, edge cases, and process feasibility before committing to solution design and build scope.
- Build working solutions quickly using real data and APIs, validate with users, and iteratively enhance for security, reliability, maintainability, and production operations.
- Create evaluation datasets with subject matter experts, perform model and LLM error analysis, and recommend improvements.
- Resolve data access, API, identity, network, security, infrastructure, and deployment blockers in collaboration with platform and engineering teams.
- Own post-go-live stabilization by monitoring services, diagnosing failures, addressing latency and cost issues, executing recovery plans when required, and delivering fixes.
- Measure adoption and business impact using usage data and agreed KPIs, and communicate outcomes through dashboards, demonstrations, and executive summaries.
- Complete structured handovers with runbooks, support ownership documentation, knowledge transfer materials, reusable components, test artifacts, and deployment patterns.
Generic Managerial Skills
- Strong problem-solving and decision-making abilities with a balanced focus on business outcomes, technology strategy, security, scalability, and operational excellence.
- Excellent communication, presentation, and stakeholder management skills, with the ability to engage effectively with business, technical, and executive audiences.
- Strong consulting mindset with the ability to analyze complex challenges, recommend practical solutions, and clearly articulate architectural trade-offs.
- Proven ability to lead and influence cross-functional, distributed teams in a collaborative and fast-paced delivery environment.
- High level of ownership, accountability, attention to detail, and commitment to engineering quality and delivery excellence.
- Strong planning, prioritization, and multitasking skills with the ability to manage multiple initiatives, stakeholders, and delivery commitments simultaneously.
- Ability to mentor engineers and architects, foster knowledge sharing, and drive adoption of engineering best practices.
- Adaptability and resilience to work effectively in rapidly evolving technologies, business priorities, and stakeholder environments.
Salary Range - CA$ 100,000 - CA$ 120,000 Per Year
TCS does not use artificial intelligence tools for candidate screening or evaluation. This post is for a current vacancy. The hiring process includes an initial screening, followed by a technical evaluation and managerial discussion.
Tata Consultancy Services Canada Inc. is committed to meeting the accessibility needs of all individuals in accordance with the Accessibility for Ontarians with Disabilities Act (AODA) and the Ontario Human Rights Code (OHRC). Should you require accommodation during the recruitment and selection process, please inform Human Resources.
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.
