forward Deployed Engineer
- Toronto, ON, Canada
Full-time
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Job details
- Job type
- Full-time
- Apply by
- Experience
- 10+ years of experience in data engineering, AI application development, cloud data platforms, and production software engineering.
- Posting language
- English
- Posted
Original job description
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.
TCS is an IT services, consulting, and business solutions organization that has been partnering with many of the world’s 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.
The opportunity
We are looking for a senior Forward Deployed Engineer who combines production-grade software engineering, data engineering, AI application development, and client-facing consulting. You will embed with business users, client SMEs, product owners, and engineering teams to understand complex workflows, rapidly validate solutions using real data, remove technical blockers, and own delivery through production launch, stabilization, adoption, and handover.
What you will do
- Embed with client SMEs, product owners, business users, and engineers to map workflows, users, data, constraints, and decision points.
- Agree on the first useful release, measurable success criteria, and a practical roadmap from prototype to production.
- Profile unfamiliar client data using Python, pandas, PySpark, and SQL to assess coverage, quality, volumes, distributions, edge cases, and feasibility.
- Build thin working solutions using real client data and APIs, validate them with users, and iteratively harden them for production.
- Design, develop, and deploy enterprise AI and data applications using Python, PySpark, SQL, REST APIs, FastAPI, and cloud data platforms.
- Build Claude-powered applications, copilots, and AI workflows using prompt engineering, RAG, vector databases, semantic search, and agentic AI patterns.
- Design batch, real-time, and streaming data pipelines and integrations across enterprise systems.
- Implement MLOps/LLMOps capabilities, including lifecycle management, CI/CD, MLflow, monitoring, deployment automation, rollback, and production support.
- Create evaluation datasets with client SMEs, measure model and LLM quality, perform structured error analysis, and prioritize improvements.
- Resolve data-access, API, identity, network, security, infrastructure, and deployment blockers with client teams.
- Own post-go-live monitoring, incident diagnosis, rollback, stabilization, latency, performance, reliability, and cost optimization.
- Measure adoption and business impact using agreed KPIs, then complete structured handover with runbooks, support ownership, and knowledge transfer.
What you bring
- 10+ years of experience in data engineering, AI application development, cloud data platforms, and production software engineering.
- Strong hands-on expertise in Python, PySpark, SQL, REST APIs, FastAPI, Git, Docker, Kubernetes, Airflow, MLflow, CI/CD, and distributed processing.
- Experience with Claude, prompt engineering, RAG, vector databases, semantic search, and agentic AI patterns.
- Strong knowledge of ETL/ELT, batch and streaming pipelines, data quality, metadata, lineage, observability, and DataOps.
- Experience operationalizing MLOps/LLMOps, including model lifecycle management, automated deployment, monitoring, rollback, and production support.
- Knowledge of enterprise cloud services across compute, storage, integration, orchestration, networking, monitoring, security, and cost optimization.
- Understanding of IAM/RBAC, encryption, secrets management, privacy controls, auditability, compliance, and secure data access.
- Ability to translate business requirements into scalable designs, define non-functional requirements, estimate effort, and drive implementation.
- BFSI experience and strong client-facing skills across discovery, rapid prototyping, solution shaping, workshops, and technical presentations.
- Bachelor's degree in a relevant discipline. Cloud, Kubernetes, AI engineering, MLOps, data engineering, architecture, or security certifications are preferred.
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.
More about this job
Responsibilities
Work with client teams to understand workflows, assess data, and build and validate AI and data solutions, taking them from prototype through production launch. Own integrations, operationalization, post-launch reliability and optimization, adoption measurement, and structured handover.
Requirements
Requires 10+ years of experience in data engineering, AI application development, cloud data platforms, and production software engineering, with hands-on expertise in the listed engineering, data, and MLOps tools. Candidates should also have enterprise cloud and security knowledge, strong client-facing and solution-design skills, BFSI experience, and a bachelor's degree in a relevant discipline; related certifications are preferred.
Skills
- Python
- PySpark
- SQL
- REST APIs
- FastAPI
- Claude
- Prompt Engineering
- Retrieval-Augmented Generation (RAG)
- Vector Databases
- Agentic AI
- Data Engineering
- MLOps/LLMOps
- Kubernetes
- Docker
- Airflow
- Client-Facing Consulting
Visa sponsorship
Not detected in the job text
Categories
- Technology
- Software
- Data & Analytics
- Consulting
- Engineering
Keywords
- Python
- PySpark
- SQL
- REST APIs
- FastAPI
- Claude
- Prompt Engineering
- Retrieval-Augmented Generation (RAG)
- Vector Databases
- Semantic Search
- Agentic AI
- ETL/ELT
- Batch Processing
- Streaming Data Pipelines
- Data Quality
- DataOps
- MLOps
- LLMOps
- MLflow
- CI/CD
- Docker
- Kubernetes
- Airflow
- Distributed Processing
- Cloud Data Platforms
- IAM/RBAC
- Encryption
- Secrets Management
- BFSI
- Production Support