Senior AI Engineer - Production & MLOps

Tata Consultancy Services Limited; Greater London; On-site; GBP 75,000 - 110,000; Full time

Job summary

Tata Consultancy Services UK is seeking a hands-on AI Engineer to build, test and deploy production‑grade AI solutions in London. You will work with the AI Delivery Architect and client teams to turn approved designs into working software across back-end, APIs and orchestration.

The role covers applied AI, software engineering, data pipelines, deployment automation and observability. You will own the build, run testing and provide reusable code, documentation and operational assets for the wider

Qualifications

• 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.
• 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.
• 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.
• 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.
• 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 related field, or equivalent professional experience

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

Skills

Python programming

REST/gRPC

CI/CD

Code comprehension

Model APIs

Agent frameworks

RAG embeddings

Failure modes

SQL

Cloud platforms

Kubernetes

LLMOps

Troubleshooting

Evaluation data

Security best practices

End-to-end ownership

Knowledge sharing

Full-stack

Streaming

Security/regulations

Conversational AI

Cloud certifications

Education requirements

Education

Bachelor’s or master’s degree in Computer Science, Engineering, Data Science or related field

Tools

React

Angular

Vue

Next.js

Job description

Tata Consultancy Services UK is seeking a hands-on AI Engineer to build, test and deploy production‑grade AI solutions in London. You will work with the AI Delivery Architect and client teams to turn approved designs into working software across back-end, APIs and orchestration.

The role covers applied AI, software engineering, data pipelines, deployment automation and observability. You will own the build, run testing and provide reusable code, documentation and operational assets for the wider