AI Engineer

Licensed sponsor London Full-time Posted 1 day ago

If you need support in completing the application or if you require a different format of this document, please get in touch with at UKI.recruitment@tcs.com or call TCS London Office number 02031552100 with the subject line: “Application Support Request”.

Role: AI Engineer

Job Type: Permanent

Location: London

Number of hours: 40 hours per week – full time

Ready to utilize your experience and expertise in AI Engineer?

We have an exciting role for you - AI Engineer!

Careers at TCS: It means more

TCS is a purpose-led transformation company, built on belief. We do not just help businesses to transform through technology. We support them in making a meaningful difference to the people and communities they serve - our clients include some of the biggest brands in the UK and worldwide. For you, it means more to make an impact that matters, through challenging projects which demand ambitious innovation and thought leadership.

Role Summary

We are looking for a hands-on AI Engineer to build, integrate, test and deploy production-grade AI solutions. The engineer works with the AI Delivery Architect, client teams, domain teams and other delivery specialists to turn an approved design into working software. The role covers applied AI, software engineering, data and knowledge pipelines, enterprise integration, deployment automation, evaluation, observability and production troubleshooting.

The role is important because a successful AI solution must work reliably beyond a demonstration. The AI Engineer owns the practical build, proves the solution through testing and telemetry, resolves technical issues and leaves behind reusable code, documentation and operational assets that the wider team can support and extend.

Pre-requisites

software, data, ML or platform engineering experience, including hands-on ownership of production or production-like systems
Strong Python programming and practical experience with at least one additional enterprise or front-end language such as Java, C#, JavaScript or TypeScript
Hands-on delivery of LLM, retrieval, agentic or ML applications beyond tutorials or isolated notebooks
Experience integrating models and AI services with enterprise applications, APIs, data sources, workflows and systems of record
Experience with version control, automated testing, code review, containers, CI/CD, logging, monitoring and secure configuration
Practical experience with at least one major cloud platform and its application, data, identity, networking, monitoring and deployment services
Ability to work directly with users, architects and engineers and take a use case from technical specification through build, test, deployment and handover

Key Responsibilities

Work with the AI Delivery Architect, client stakeholders and domain teams to convert approved requirements into technical specifications, tasks, acceptance criteria and working increments
Build and deploy AI-enabled applications and services across back-end, APIs, orchestration and, where required, front-end components
Develop AI agents and sub-agents using appropriate patterns for planning, routing, tools, memory, state, delegation, human approval and safe failure handling
Build data, retrieval and context pipelines for structured and unstructured content, including ingestion, parsing, chunking, metadata, indexing, vector or hybrid search, ranking, filtering and evidence traceability
Integrate model endpoints and gateways, and implement prompt, model and configuration versioning, routing, fallback and environment-specific settings
Build and maintain data ingestion and transformation pipelines with validation, data-quality checks, metadata, lineage and schema-change handling
Build governed integrations using REST or gRPC APIs, MCP, microservices, queues, events or streams, and enterprise systems
Implement authentication, authorization, secrets, validation, idempotency, retries, rate limits, error handling, compensation and audit logging for AI-enabled actions
Write clean, modular, testable, observable and maintainable code, supported by unit, integration, regression, security and performance tests
Create evaluation datasets and automated tests for retrieval quality, groundedness, task success, policy adherence, tool selection, safety, latency, cost and end-to-end outcomes
Instrument models, retrieval, agents, tools, integrations and applications with logs, metrics, traces, dashboards and alerts; use the resulting evidence to diagnose failures
Build and maintain deployment pipelines, containers, infrastructure configuration, release controls, rollback procedures and operational runbooks
Tune reliability, availability, throughput, latency and cost using caching, routing, context control, scaling and deterministic fallbacks where appropriate
Contribute reusable code, agent templates, prompt and tool contracts, connectors, evaluation assets, reference implementations and engineering documentation
Demonstrate working software, participate in design and code reviews, support deployment and troubleshooting, and transfer knowledge to the wider team

Required Skills & Qualifications

Software & Integration Engineering

Strong Python programming, API development and integration skills
REST or gRPC, microservices, authentication, asynchronous or event-driven processing, databases and object storage
Version control, automated testing, code review, CI/CD, Docker or similar containers and secure configuration
Ability to understand unfamiliar code, isolate defects and explain implementation decisions

Applied AI & Agent Engineering

Model APIs or enterprise model services, structured outputs, prompt and configuration management, tool or function calling and context handling
Agent frameworks or equivalent orchestration approaches covering state, memory, retries, permissions and human checkpoints
RAG and knowledge applications using embeddings, vector or hybrid search, metadata, ranking, access-aware retrieval and evaluation
Understanding of model and agent failure modes, prompt injection, hallucination, data leakage and safe fallback patterns

Data, Platform & Production Operations

SQL and data-engineering skills for ingestion, transformation, data quality, metadata and schema evolution
Cloud-native application and data services on AWS, Microsoft Azure or Google Cloud
Kubernetes or managed container services, IaC, identity, networking, secrets, logging and monitoring
MLOps or LLMOps practices covering versioning, automated evaluation, deployment, monitoring and rollback
Ability to troubleshoot across data, retrieval, models, prompts, orchestration, integrations, infrastructure, performance and security

Quality, Security & Professional Skills

Creation of representative evaluation data, quality measures, thresholds, regression tests and release evidence
Least-privilege access, masking or redaction, guardrails, audit evidence and secure tool execution
Clear communication of progress, limitations, decisions and risks to technical and nontechnical stakeholders
Ownership of end-to-end outcomes, with balanced attention to speed, maintainability, security, reliability and cost
Knowledge sharing through pairing, reviews, demonstrations, documentation and reusable examples

Preferred Qualifications

Full-stack engineering experience with React, Angular, Vue, Next.js or comparable frameworks
Experience with streaming, distributed processing, analytical platforms, knowledge graphs or document intelligence
Experience in regulated, security-sensitive or high-availability environments
Experience with conversational or voice AI, contact-center integration or multimodal applications
Relevant cloud developer, AI engineer, data engineer, DevOps, Kubernetes or application-security certification
Bachelor’s or master’s degree in Computer Science, Engineering, Data Science or a related field, or equivalent professional experience

What Success Looks Like

The engineer converts the approved design into stable, testable and observable working software
Data, retrieval, model, integration and deployment components work together reliably in the target environment
Evaluation and telemetry provide evidence for release decisions and ongoing improvement
Reusable code and documentation reduce effort and risk for subsequent AI use cases
The wider team can independently build, deploy, troubleshoot and extend the solution after the incubation phase

Rewards & Benefits

TCS is consistently voted a Top Employer in the UK and globally. Our competitive salary packages feature pension, health care, life assurance, laptop, phone, access to extensive training resources and discounts within the larger Tata network.

We offer health & wellness initiatives and sports events; we are the proud sponsor of the London Marathon.

Diversity, Inclusion and Wellbeing

Tata Consultancy Services UK&I is committed to meeting the accessibility needs of all individuals in accordance with the UK Equality Act 2010 and the UK Human Rights Act 1998.

We welcome and embrace diversity in race, nationality, ethnicity, disability, neurodiversity, gender identity, age, physical ability, gender reassignment, sexual orientation. We are a disability inclusive employer and encourage disabled people to apply for this role.

As a Disability Confident Employer, we offer an interview to applicants with disabilities or long-term conditions who meet the minimum criteria for the role. Please email us at UKI.recruitment@tcs.com if you would like to opt in.

If you are an applicant who needs any adjustments to the application process or interview, please contact us at UKI.recruitment@tcs.com with the subject line: “Adjustment Request” or call TCS London Office 02031552100 / +44 204 520 2575 to request an adjustment. We welcome requests prior to you completing the application and at any stage of the recruitment process.

Next Steps:

Application Process

Online application: You can apply directly through LinkedIn/ by uploading your CV. In case you wish to submit your application via another format like audio/video, please, contact - UKI.recruitment@tcs.com
Skill-Based discussion: This will be a level 1 interview with the project team, it can be via video or in-person. Details will be confirmed by your recruiter.
Managerial discussion: This discussion will focus on behavioural aspects and person-organisation fit.
HR Discussion: This will be with one of the members of the HR team and will cover your career journey, aspirations for growth, compensation and any other questions you may have.

Beware of Fraudulent offers

This is to notify you that TCS does not ask for any sort of payment or security deposit from candidates at any stage of the recruitment process. The firm never sends out job offers from free internet email services like Gmail, Yahoo Mail, and so on. TCS has not authorised any third-party company to collect money on their behalf. As a vigilant job seeker, beware of fraudulent recruitment activity and protect your interests! You can write to UKI.recruitment@tcs.com to report any fraudulent activity.

Due to the high volume of applications, we will be unable to contact each applicant individually on the status of their application. If you have not received a direct response within 30 days, then it should be deemed unsuccessful on this occasion.

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