AI Engineer in Stratford-upon-Avon

At Tata Technologies we make product development dreams a reality by designing, engineering and validating the products of tomorrow for the world’s leading manufacturers. Due to our continued growth we are now recruiting for an AI Engineer to be based at our customer site in Gaydon.

Our Embedded Systems Solutions department (ESS) encompasses all activities outlined under the Automotive SPICE (ASPICE) process framework, including systems engineering, software engineering, coding, and all levels of functional testing. Beyond core development, ESS also integrates critical supporting processes such as project management, risk assessment, functional safety, and cybersecurity, ensuring compliance with ASPICE standards and delivering reliable, secure, and high-quality embedded systems & solutions.

Role Summary:

Tata Technologies is looking for a hands-on AI / GenAI Application Engineer to design, develop, enhance and scale enterprise AI applications using Large Language Models (LLMs) and the Databricks AI ecosystem.

Dimension of function:

The successful candidate will work on existing AI solutions as well as new use cases, taking responsibility for application development, integration, maintenance, troubleshooting and scalability. The role requires strong Python software engineering skills combined with practical experience developing LLM-based applications and working with cloud platforms such as Azure and AWS.

The engineer will help transition AI solutions from early-stage implementations and proofs of concept into robust, maintainable and scalable applications.

Areas of responsibility:

AI / GenAI Application Development

· Design, develop and enhance LLM-based applications and AI agents using models available through Databricks.

· Develop reusable AI application components and workflows using Python.

· Build new AI capabilities and enhance existing GenAI use cases based on business and engineering requirements.

· Develop agent-based solutions capable of integrating multiple tools, APIs and enterprise data sources.

· Support model-agnostic application architectures where different LLMs can be adopted as needed.

Existing Application Maintenance & Enhancement

· Take ownership of existing AI applications and associated Python components.

· Maintain, troubleshoot and enhance current solutions.

· Analyse application issues and implement appropriate fixes and improvements.

· Refactor existing code to improve maintainability, reliability and scalability.

· Manage technical improvements as solutions mature from prototype into production-oriented applications.

· Support feature enhancements and onboarding of new AI use cases.

Python & Backend Engineering

· Develop high-quality, modular and maintainable Python code.

· Develop backend application components and APIs supporting AI functionality.

· Implement appropriate exception handling, logging, configuration and testing.

· Conduct debugging, code optimisation and peer code reviews.

· Develop automated tests for business-critical AI application components.

Databricks & LLM Engineering

· Develop AI applications within the Databricks ecosystem, with hands-on exposure to Databricks AI capabilities preferred.

· Integrate LLM services with application workflows and enterprise datasets.

· Support model configuration and integration within AI applications.

· Work with appropriate data and AI services within the Databricks environment.

· Contribute to scalable patterns for deploying and managing multiple AI use cases.

Enterprise Systems Integration

· Integrate AI applications with enterprise systems through REST APIs and other service interfaces.

· Develop AI agents capable of retrieving and processing information from business and engineering systems.

· Support integration with enterprise knowledge and data sources.

· Develop reusable integration components to accelerate future AI use cases.

Cloud & Scalability

· Support AI application deployment and operation across Azure, AWS and Databricks environments.

· Work with Cloud/DevOps engineers to improve deployment, scalability and operational reliability.

· Support increasing user volumes and application workloads.

· Contribute to CI/CD and automated deployment processes.

· Identify and resolve application performance and scalability issues.

Production & Operational Support

· Support the transition of AI solutions from PoC/prototype to production-ready applications.

· Implement appropriate testing and validation of AI workflows.

· Support application monitoring, issue investigation and root-cause analysis.

· Improve solution robustness based on operational data and user feedback.

· Maintain appropriate technical and application documentation.

· Follow software engineering best practices for version control, release management and configuration management.

Knowledge, Skills & Experience (essential)

The successful candidate should demonstrate:

· Strong hands-on Python software development experience.

· Practical experience developing AI/GenAI applications using LLMs.

· Experience developing and maintaining enterprise software applications.

· Understanding of LLM application architecture and agent-based AI solutions.

· Experience integrating applications with REST APIs and external systems.

· Good knowledge of cloud platforms, particularly Azure and/or AWS.

· Ability to troubleshoot, maintain and enhance existing codebases.

· Understanding of software development lifecycle, version control and testing.

· Experience designing solutions with scalability, reliability and maintainability in mind.

Knowledge / Experience (desirable)

Experience in one or more of the following would be advantageous:

· Hands-on experience with Databricks.

· Databricks AI/GenAI capabilities.

· Agentic AI / AI agent development.

· Retrieval-Augmented Generation (RAG) architectures.

· Enterprise knowledge retrieval solutions.

· Databricks Unity Catalog.

· MLflow or AI/ML lifecycle management.

· CI/CD and DevOps.

· Data engineering and data architecture.

· Azure AI services.

· AWS AI/cloud services.

· Integration with enterprise engineering tools such as Jira or Polarion.

In return for bringing your expertise to our business we offer a competitive salary along with excellent benefits including:

· Pension Scheme – We match employee contribution up to 5% of salary

· 25 Days’ Holiday

· Private Health Care

· Tata Jaguar Land Rover Privilege Scheme - up to 20% off new JLR vehicles

· Group Income Protection

· Health Assured – Employee Assistance Program

· Group Life Assurance

· Health Shield – Private Health Cash Plan

If you are passionate about bringing innovation to the projects you work on and want to join a global company, then this is the place for you.

Tata Technologies: Engineering a better world.

Tata Technologies would like to thank all applicants for their interest, each application will be reviewed against the set criteria for the role. We would like to advise that only candidates under consideration will be contacted. If you do not hear from us within 10 working days following the closing date it will mean that unfortunately your application has not been successful. We will however retain your details for any suitable future opportunities.