Cloud and AI Engineering Lead

Job Role: Cloud and AI Engineering Lead
Location: Bangalore

ABOUT UNILEVER
With 3.4 billion people in over 190 countries using our products every day, Unilever is a business that makes a real impact on the world. Work on brands that are loved and improve the lives of our consumers and the communities around us. We are driven by our purpose: to make sustainable living commonplace, and it is our belief that doing business the right way drives superior performance. At the heart of what we do is our people – we believe that when our people work with purpose, we will create a better business and a better world.
At Unilever, your career will be a unique journey, grounded in our inclusive, collaborative, and flexible working environment. We don’t believe in the ‘one size fits all’ approach and instead we will equip you with the tools you need to shape your own future.

ABOUT GDT:

GDT is the global digital and technology engine of Unilever offering business services, technology, and enterprise solutions. GDT serves over 190 locations and through a network of specialized service lines and partners delivers insights and innovations, user experiences and end-to-end seamless delivery making Unilever Purpose Led and Future Fit. 

About Us:
Wild are on a mission to remove single-use plastic from the bathroom, armed with our refillable, natural and scent-sational deodorants, body wash, and lip balm – and we’re only just getting started. We launched in 2020 and as a high-growth company we’re already one of Europe’s fastest growing start-ups.

Role Summary
Wild is moving from chat-based AI usage toward a portfolio of autonomous AI agents that automate real business workflows. The Lead Manager – AI Platform & Engineering owns the technical vision, the cloud platform, and the engineering function that will make this shift happen — designing and running a scalable, secure, and governed agent platform on Google Cloud Platform (GCP) and Google Agent Builder, grounded in Wild's Snowflake data estate.
This is a hands-on, cloud-centric role, not a purely administrative one. You will own the GCP landing zone and platform operations, lead end-to-end solution design for Agentic use cases, and define the engineering standards, guardrails, and assurance practices the team works to. You will lead a small multidisciplinary team of Agentic AI developers, data engineers, and FinOps, translating Wild's business priorities — across a fast-growing sustainable personal care brand — into a prioritised agent roadmap, while ensuring everything built is production-grade, observable, cost-aware, and compliant from day one.
As the technical voice in the team, you are also a bridge to stakeholders in security, privacy, and Unilever's wider Digital & Technology organisation. You balance speed of delivery with enterprise discipline — embedding AI assurance, data privacy, and responsible-AI controls into the platform so the team can ship value quickly and safely at scale.

Key Responsibilities
• Own the GCP cloud platform end to end: landing zone, project/environment structure, IAM, networking, security baseline, and platform operations (reliability, observability, and lifecycle management).
• Lead solution design and architecture for AI use cases on GCP and Google Agent Builder — orchestration, tool/function calling, memory, retrieval (RAG), and integration patterns — producing reference architectures and reusable platform building blocks.
• Define and enforce engineering standards — CI/CD, infrastructure-as-code, version control, testing, prompt/agent evaluation, observability, and release management.
• Deliver architecture solutions through all phases of the product lifecycle, including requirements definition, architecture design, implementation, and testing using proven agile methodologies.
• Provide comprehensive designs and technical guidance for engineers on how to deliver programmatic elements of the implementation as part of defined product services.
• Architect cloud-native, hybrid, or multi-cloud solutions to meet Wild’s needs.
• AI assurance: model/agent evaluation frameworks, accuracy and safety testing, bias and hallucination controls, human-in-the-loop design, and ongoing monitoring of agents in production.
• Embed data privacy and protection by design: PII handling, data residency, access control, anonymisation/minimisation, and compliance with GDPR/UK data-protection requirements in partnership with privacy and legal teams.
• Establish governance and guardrails: responsible-AI controls, auditability, and full model/agent lifecycle management.
• Document developed processes, procedures, and architectural decisions.
• Demonstrate understanding of the current technology environment and industry trends.
• Build and lead the engineering team: line management, hiring, capability development, and performance for AI developers, data engineers, and FinOps.
• Set the agent roadmap in partnership with the business; prioritise use cases by value, feasibility, and risk.
• Embed cost discipline by partnering with FinOps to design for efficiency (infrastructure rightsizing, model selection, caching, token optimisation) before scaling.
• Report on delivery, adoption, platform health, risk, and value realised.

Required Skills & Experience
• 8+ years in software, data, ML, or cloud engineering, with 3+ years leading technical teams.
• Strong hands-on GCP platform expertise: landing zone design, IAM, networking, security, Vertex AI / Agent Builder, and cloud-native services — ideally with infrastructure-as-code (Terraform).
• Experience with cloud-native technologies including the design and automation of Infrastructure as a Service (IaaS) deployments using deployment strategies such as blue-green.
• Experience designing Platform as a Service (PaaS) capabilities to improve new or existing environments.
• Skilled in creating and reviewing designs based on code that deploys virtual networks, virtual machines, cloud services, container services, operating system services, web services, and data services.
• Previous ownership of the technical solution architecture.
• Proven solution-design and architecture capability, delivering production AI/ML or LLM-based systems end to end — not just prototypes.
• Solid understanding of agentic architectures: RAG, orchestration, tool use, evaluation, and guardrails.
• AI assurance expertise: model/agent evaluation, accuracy/safety testing, responsible-AI frameworks, and production monitoring.
• Strong grasp of data privacy and protection (GDPR/UK GDPR, PII handling, data residency) and how to engineer it into AI platforms.
• Familiarity with modern data platforms (Snowflake, warehousing, pipelines) and how they feed AI systems.
• Demonstrated ownership of security, governance, and scalability in an enterprise context.
• Excellent stakeholder management and the ability to translate business needs into technical roadmaps.

Preferred Qualifications
• GCP Professional certification (Cloud Architect or ML Engineer) and/or recognised security/privacy credentials.
• Experience standing up or operating a cloud platform / landing zone for an enterprise or acquired business.
• Exposure to AI assurance, model-risk, or responsible-AI governance frameworks.
• Experience in CPG, retail, or consumer brands; comfort operating in a post-acquisition or scale-up environment.
• Bachelor's or Master's in Computer Science, Engineering, or a related field.

Key Success Metrics
• Number of agents promoted to production and sustained (e.g. 6–10 within the first 12 months).
• Platform health: agent task success rate and platform uptime ≥ 99.5%.
• Solution-design throughput: time-to-production for a new agent use case (target trend: months to weeks).
• Assurance coverage: 100% of production agents covered by evaluation, monitoring, and safety controls.
• Privacy & governance: 100% of AI workloads compliant with data-privacy and access-control standards, with zero critical findings.
• Adoption: percentage of targeted workflows automated and active business users.
• Cost efficiency: cost-per-automated-task trending down quarter-on-quarter (jointly with FinOps).

Collaboration & Stakeholders
• Wild tech & AI programme lead.
• Wild business and function leads.
• Unilever Global Digital & Technology, security, and architecture teams.
• The AI Developer, Data Engineer, and FinOps Manager (direct team).
• Data governance and procurement.

Why This Role Matters
This role is the linchpin of Wild's AI transformation. Without strong technical leadership, agent initiatives stall at the proof-of-concept stage. By combining architectural ownership, engineering leadership, and enterprise discipline, this role converts AI ambition into governed, scalable automation that frees human capacity for higher-value work.

LEADERSHIP SKILLS

• CARE DEEPLY: We care about how consumers experience our brands, the growth and development of our people, and their impact on the planet. We emphasize the importance of performance and care, moving from ambiguity about success to fairness and transparency. 

• FOCUS ON WHAT COUNTS: We prioritize what truly matters, setting clear and stretching goals. We aim to shift from having everything as a priority to focusing on fewer, bigger things that are delivered to conclusion and are being rewarded. 

• STAY THREE STEPS AHEAD: We encourage bold and creative thinking to make breakthroughs in performance. We focus on anticipating and staying ahead of consumer needs and external trends, shifting from reacting to leading, shaping, and disrupting the market. 

• DELIVER WITH EXCELLENCE: The emphasis is on delivering everything with excellence and pace, taking personal ownership, and holding each other accountable. We aim to shift from pride in thinking to pride in execution, developing breakthrough solutions and ensuring the best outcomes. 

Our commitment to Equality, Diversity & Inclusion 

• Unilever embraces diversity and encourages applicants from all walks of life! This means giving full and fair consideration to all applicants and continuing development of all employees regardless of age, disability, gender reassignment, race, religion or belief, sex, sexual orientation, marriage and civil partnership, and pregnancy and maternity.