Tata Consultancy Services
AI Delivery Architect
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Role: AI Delivery Architect
Job Type: Permanent
Location: London
Number of hours: 40 hours per week – full time
Ready to utilize your experience and expertise in AI Delivery Architect?
Role Summary
We have an exciting role for you - AI Delivery Architect!
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.
We are looking for an experienced AI Delivery Architect to design enterprise AI solutions, validate their implementation and work with engineering teams to drive execution. This is a hands-on delivery role, not an advisory-only architecture position. The architect converts business objectives and domain inputs into an implementable solution, makes the key technical decisions, guides the engineering team and remains accountable for the technical integrity of the delivery.
The role is important because complex AI programs bring uncertainty across models, data, integration, security, evaluation and operations. The architect provides one coherent design, makes trade-offs visible, reduces technical risk and ensures that the resulting solution is secure, reusable, observable and ready for production.
Pre-requisites
- Technology experience, including architecture and technical delivery of enterprise solutions and recent hands-on experience with AI-enabled systems beyond PoC
- Strong solution architecture foundation across applications, data, APIs and integration, cloud, security, deployment and operations
- Hands-on understanding of GenAI and agentic AI, including LLMs, RAG, context engineering, tool use, orchestration, memory and human-in-the-loop (HITL) controls
- Experience designing production-grade integrations with enterprise systems using APIs, microservices, events, streams or queues
- Experience defining evaluation, testing, observability, security, responsible AI, reliability, performance and cost controls for AI solutions
- Practical experience with at least one major cloud platform and its AI, data, identity, networking, monitoring and deployment services
- Ability to lead multidisciplinary delivery teams, review critical implementation, communicate technical trade-offs and transfer ownership to the wider delivery organization
Key Responsibilities
- Design the end-to-end AI solution across application, model, data, context, integration, security, deployment, evaluation, observability and operations
- Translate business objectives and domain-team inputs into solution boundaries, architecture decisions, technical roadmaps, NFRs and measurable acceptance criteria
- Select appropriate AI patterns, models, platforms and implementation approaches based on quality, safety, latency, cost, data sensitivity, maintainability and operational risk
- Define architecture for AI agents, orchestration, tool invocation, memory, retrieval, model abstraction, governed execution and human escalation
- Define the data and knowledge approach, including ingestion, metadata, lineage, access-aware retrieval, ranking, freshness and evidence traceability
- Define reusable integration patterns for APIs, MCP, microservices, events, enterprise systems and legacy platforms, including authentication, authorization, idempotency and failure handling
- Define standards for model gateways, routing, prompt and configuration versioning, environment promotion, release controls and rollback
- Define the evaluation strategy, test coverage, quality thresholds and release gates across retrieval, prompts, models, agents, tools and end-to-end outcomes
- Define end-to-end observability covering model calls, retrieval, orchestration, tools, data pipelines, latency, usage, cost, errors and audit events
- Define production-readiness requirements for scalability, availability, resilience, DR, security, privacy, responsible AI and ongoing support
- Validate implementation through architecture reviews, critical code and design reviews, technical walkthroughs and production-readiness checks
- Resolve cross-team technical risks and work with engineers to ensure the agreed design is implemented effectively
- Create reusable reference architectures, ADRs, interface contracts, engineering patterns, playbooks and operational guidance
- Coach engineers through paired design and reviews, and progressively transfer architecture and operational knowledge to the wider team
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Required Skills & Qualifications
Architecture & Delivery Leadership
- Solution and enterprise architecture across cloud-native, hybrid and legacy environments
- Architecture governance, technical design authority, ADRs and NFRs
- Ability to convert ambiguous requirements into an executable design and phased delivery plan
- Ability to review implementation and diagnose issues across application, data, integration and platform layers
AI, Data & Platform Engineering
- LLMs, structured outputs, prompt and configuration management, grounding and common failure modes
- Agentic patterns covering planning, routing, delegation, tools, state, memory, durable workflows and human approval
- RAG, semantic or hybrid search, vector databases, metadata, knowledge graphs and access-aware retrieval
- Data ingestion, data quality, metadata, lineage and schema evolution
- Cloud services, containers, Kubernetes, IaC, CI/CD, identity, secrets, networking, logging and monitoring
- MLOps or LLMOps practices covering versioning, deployment, evaluation, monitoring and rollback
AI Quality, Governance & Operations
- Evaluation of groundedness, task success, policy adherence, tool selection, safety, latency and cost
- Responsible AI, privacy, security, explainability, auditability and human accountability
- Operational resilience, performance, capacity, incident response and production-support readiness
- Metrics, logs, traces, dashboards and alerts across the complete AI service
Leadership & Professional Skills
- Clear communication with business, architecture, engineering, security, risk and operations stakeholders
- Decisive, evidence-based judgement in ambiguous delivery situations
- Ability to surface risks and limitations without slowing execution unnecessarily
- Strong collaboration, mentoring and influencing skills across distributed teams
- Balanced focus on delivery outcome, engineering quality, cost, risk and maintainability
Preferred Qualifications
- Architecture leadership in regulated, security-sensitive or high-availability environments
- Experience creating reusable AI platform patterns, agent control planes or engineering standards
- Experience with multi-model, hybrid, on-premises or sovereign AI environments
- Relevant cloud solution architect certification from AWS, Microsoft Azure or Google Cloud
- Relevant AI, ML, data, security, Kubernetes or service-management certification
- Bachelor’s or master’s degree in Computer Science, Engineering, Data Science, Mathematics or a related field, or equivalent professional experience
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What Success Looks Like
- The solution design is implementable and guides delivery rather than remaining conceptual
- Implementation conforms to the agreed architecture and reaches production with appropriate quality and controls
- Reusable patterns reduce effort and technical risk for subsequent AI use cases
- The wider delivery team can independently extend, operate and govern 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
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