AI Agent Developer / Full Stack Engineer
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AI Agent Developer / Full Stack Engineer
Location
Uniops Bangalore Centre
Experience
Mid
Posted
Jul 10, 2026
Apply by
July 14, 2026
Applicants
0
Early applicantEasy applyFull-timeWork from Office
Job Description
Job Role: AI Developer / Full Stack EngineerLocation: 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 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:
The AI Developer / Full Stack Engineer is the primary builder of Wild's autonomous agents and the applications around them. Where the business today uses LLMs in a chat-based way, this role designs and ships agents that take action — calling tools and APIs, executing multi-step workflows, and operating with minimal human intervention.
You will work end-to-end: designing agent logic in Google Agent Builder, integrating with Snowflake and business systems, and building the interfaces and services that let users interact with and supervise agents. This is a deeply hands-on engineering role for someone who enjoys turning ambiguous business problems into working, reliable software.
Quality and trust are central. You will build with evaluation, observability, and guardrails in mind, ensuring agents behave predictably, fail safely, and keep humans in control where it matters. You will iterate quickly, but always toward production-grade outcomes.
Key Responsibilities:
• Design, build, and deploy AI agents on Google Agent Builder, including prompts, tools/functions, orchestration, and memory.
• Develop full-stack applications — front-end interfaces and back-end services/APIs — that expose and supervise agent capabilities.
• Integrate agents with Snowflake, internal systems, and third-party APIs to enable real task execution.
• Implement retrieval (RAG) against Wild's data to ground agent responses and actions.
• Build evaluation and testing harnesses for agent accuracy, safety, and regression control.
• Instrument observability — logging, tracing, and metrics for agent behaviour and performance.
• Apply guardrails and human-in-the-loop patterns for sensitive or high-impact actions.
• Optimise for performance and cost in collaboration with FinOps (model choice, caching, token-efficient design).
• Support responsible AI practices and governance
• Implement event-driven and API-based integrations (microservices patterns)
Required Skills & Experience
• 5+ years in software engineering with strong full-stack capability (e.g. Python/TypeScript; React or similar front-end).
• 3+ years hands-on experience building LLM-powered or agentic applications (tool calling, RAG, orchestration frameworks).
• Practical experience with GCP and ideally Vertex AI / Google Agent Builder.
• Strong API design and systems integration skills.
• Comfort working with data sources such as Snowflake and writing performant SQL.
• Familiarity with prompt engineering, agent evaluation, and safe-deployment practices.
• Solid software hygiene: Git, CI/CD, testing, and code review.
• Understanding of multi-agent systems and distributed architectures
• Familiarity with LLMOps / GenAIOps concepts
• Exposure to event-driven and scalable cloud systems
• Experience in scaling and optimization of LLM systems
• Experience using AI delivery tools like Claude Code, Antigravity etc
Preferred Qualifications
• Experience with agent frameworks/enterprise AI platforms/ orchestration and vector search/embeddings.
• Exposure to cloud cost optimisation / FinOps practices
• GCP associate or professional certification.
• Prior work shipping AI features to real users in production.
• Bachelor's in Computer Science, Software Engineering, or equivalent practical experience.
Key Success Metrics
• Agents/features shipped to production and adopted by business users.
• Agent task success rate and reduction in error/escalation rates over time.
• Cycle time from use-case definition to a deployed, evaluated agent.
• Reliability: defect/incident rate post-release kept within agreed thresholds.
• Efficiency contribution: measurable reduction in token/compute cost per task through engineering choices.
Collaboration & Stakeholders
• Lead Manager – AI Platform & Engineering (direction and standards).
• Data Engineer (data access and quality).
• FinOps Manager (cost optimisation).
• Business users and process owners who define and validate workflows.
Why This Role Matters
This role is where AI ambition becomes working automation. By building reliable, well-governed agents that act on Wild's behalf, the AI Developer directly delivers the capacity gains and productivity improvements that justify the team's existence — moving the business from “AI as an assistant” to “AI that does the 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.
Key Responsibilities
- Design, build, and deploy AI agents on Google Agent Builder including prompts, tools, and orchestration.
- Develop full-stack applications with front-end interfaces and back-end services to expose agent capabilities.
- Integrate agents with Snowflake, internal systems, and third-party APIs for task execution.
- Implement retrieval-augmented generation (RAG) to ground agent responses.
- Build evaluation and testing harnesses for agent accuracy, safety, and regression control.
- Instrument observability through logging, tracing, and metrics for agent behavior.
- Apply guardrails and human-in-the-loop patterns for sensitive actions.
- Optimize for performance and cost in collaboration with FinOps.
- Support responsible AI practices and governance.
- Implement event-driven and API-based integrations using microservices patterns.
Skills Required
PythonTypeScriptReactGoogle Cloud PlatformVertex AIGoogle Agent BuilderSnowflakeSQLAPI designSystem integrationPrompt engineeringGitCI/CDLLMOpsGenAIOpsClaude CodeAntigravityProblem solvingAttention to detailCollaborationAgent frameworksEnterprise AI platformsOrchestrationVector searchEmbeddingsCloud cost optimizationFinOps
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