Senior AI Engineer – (Manager) BIP xTech

Key Responsibilities

• Design, develop, and deploy production-grade AI and ML solutions, including GenAI and LLM-enabled systems.
• Shape AI solution architectures, selecting appropriate patterns (e.g. batch vs streaming, RAG, feature stores, model serving).
• Lead AI/ML workstreams end-to-end, including planning, delivery governance, and stakeholder management.
• Mentor and support AI engineers, data scientists, and software engineers, fostering high engineering standards and collaboration.
• Implement secure, scalable deployment patterns aligned with governance, compliance, and Responsible AI expectations.
• Embed monitoring, evaluation, and continuous improvement across AI solutions.
• Collaborate closely with Data Engineers, Cloud/Data Architects, and Software Engineers to deliver coherent platforms.
• Contribute to pre-sales, discovery, and proposal development by shaping solution options and delivery approaches.
• Build strong relationships with clients and partners, acting as a trusted technical advisor.
• Experience & Capability
• 3+ years’ experience delivering AI and ML solutions in production environments.
• Demonstrated experience delivering GenAI and LLM-based solutions from prototype through to production.
• Strong Python engineering skills, with a focus on quality, testing, and maintainability.
• Solid foundations in machine learning concepts, evaluation techniques, and statistical fundamentals.
• Experience working with Databricks and one or more major cloud platforms (Azure, AWS, or GCP).
• Strong understanding of security-by-design, including access control, secrets management, and secure networking.
• Ability to align AI solutions with governance, compliance, and Responsible AI requirements.
• Proven experience leading delivery and coordinating multidisciplinary engineering teams.
• Desirable
• Practical experience implementing MLOps and LLMOps practices (CI/CD, automated testing, model lineage, reproducibility).
• Experience with infrastructure automation and platform engineering (e.g. Terraform, Docker, Kubernetes).
• Experience creating reusable engineering assets and accelerators.
• Experience working in regulated environments.
• Relevant certifications (e.g. Azure AI Engineer, Azure Data Scientist, AWS Machine Learning – Specialty).
• Eligibility for, or existing, UK Security Clearance (BPSS/SC/DV).
• Working at BIP
• Hybrid working, with regular time in a BIP office and at client sites as required.
• Opportunity to work at the forefront of applied AI delivery within a growing Centre of Excellence.
• A culture that encourages innovation, collaboration, and ownership.