Applied AI Engineer

Applied AI Engineer

Drive enterprise AI innovation, intelligent automation and production-grade Generative AI solutions by designing autonomous agents, scalable Retrieval-Augmented Generation (RAG) pipelines and intelligent AI-powered applications across enterprise platforms.

Opportunity to be one of our first team members in Woolworths Group India in Bangalore.

Woolworths Group India is partnering exclusively with Zinnov Group to recruit for this position.

About this role

As an Applied AI Engineer, you will be a key member of a unified, dual-shore Applied AI team, actively contributing to the discovery, design, development and deployment of enterprise AI solutions. Working closely with onshore Platform Managers, Architects and cross-functional engineering teams, you will help transform emerging AI capabilities into scalable, secure, governed and production-ready applications.

With a strong focus on Agentic AI, Generative AI, Retrieval-Augmented Generation (RAG) and intelligent automation, you will go beyond implementing predefined requirements. You will proactively identify opportunities, experiment with emerging technologies, shape technical solutions and take shared ownership of AI products from initial prototyping through to production deployment and continuous improvement.

You will play an important role in building reusable enterprise AI capabilities that enable intelligent decision-making, automate complex business workflows and deliver measurable business outcomes.

What you'll do

Agentic AI & Workflow Engineering: Design, develop and maintain autonomous AI agents, multi-agent orchestration workflows, tool-calling functions and Model Context Protocol (MCP) integrations to automate complex enterprise processes and enable end-to-end intelligent execution.

Generative AI & RAG Engineering: Build, integrate and optimise LLM-powered applications and Retrieval-Augmented Generation (RAG) pipelines using vector embeddings, semantic search, chunking strategies, vector schemas and context management to deliver accurate, grounded and reliable AI outputs.

AI Innovation & Product Discovery: Partner with Platform Managers and Architects during early-stage technical discovery to evaluate feasibility, explore agentic patterns, challenge assumptions and shape solution approaches. Proactively identify automation opportunities, experiment with emerging GenAI technologies and develop rapid prototypes.

Software Engineering & Platform Integration: Develop scalable, production-grade AI applications and microservices using Python, FastAPI and Pydantic. Integrate AI capabilities with enterprise systems through REST/GraphQL APIs, webhooks and distributed service architectures.

Cloud & DevOps Engineering: Build, deploy and manage AI applications across cloud-native environments, leveraging GCP Vertex AI, BigQuery, Cloud Run, Docker, Kubernetes and automated CI/CD pipelines.

AI Evaluation & AgentOps: Establish automated evaluation frameworks, golden datasets, regression testing suites, telemetry and observability mechanisms to measure AI performance, identify model drift and detect hallucinations and agent failure modes.

AI Governance & Guardrails: Implement responsible AI practices, safety controls, policy-based guardrails, audit logging and data privacy mechanisms to ensure secure, compliant and reliable AI applications in production.

Enterprise Knowledge & Context Integration: Collaborate with Data Engineers and Semantic Engineers to integrate structured enterprise data, semantic models, knowledge graphs and graph topologies into agent-ready context, improving the quality and relevance of AI-generated responses.

Production Quality & Continuous Improvement: Take shared accountability for AI product health, reliability, adoption and business impact. Monitor production feedback, investigate performance issues and continuously enhance deployed AI solutions.

Cross-Shore Collaboration: Work as an integral member of a dual-shore Agile squad, collaborating with onshore Platform Managers, Architects, Lead Engineers and business stakeholders. Actively contribute to architectural discussions, technical design, code reviews, sprint delivery and shared product outcomes.

What you'll bring

Agentic AI & Generative AI Expertise: Demonstrated experience building and deploying production-grade LLM applications, autonomous agents, multi-agent systems, tool calling, function calling and agent orchestration workflows.

RAG & Context Engineering: Strong understanding of Retrieval-Augmented Generation, vector embeddings, semantic search, vector databases, chunking strategies, context windows and enterprise knowledge grounding techniques.

AI Frameworks & Technologies: Hands-on experience with AI orchestration frameworks and emerging technologies such as LangChain, Model Context Protocol (MCP), GCP ADK and equivalent agent development frameworks.

Software Engineering & API Development: Strong proficiency in Python, FastAPI, Pydantic, REST/GraphQL APIs, microservices and software engineering best practices, with the ability to build maintainable and scalable production applications.

Cloud & Platform Engineering: Practical experience with cloud platforms, preferably Google Cloud Platform (GCP), including Vertex AI, Vertex AI Search, BigQuery and Cloud Run.

DevOps & Productionisation: Proven experience transitioning AI proofs of concept and experimental solutions into production applications using Docker, Kubernetes, CI/CD pipelines, GitHub Actions, automated testing and deployment practices.

AI Evaluation & Observability: Experience implementing LLM evaluation frameworks, golden test datasets, regression suites, telemetry, model monitoring, hallucination detection and AI safety guardrails.

Enterprise Data & Knowledge Integration: Ability to collaborate with Data Engineers and Semantic Engineers to consume structured data products, semantic models, knowledge graphs and enterprise data architectures to enrich AI agent context.

Product & Innovation Mindset: Demonstrated initiative, curiosity and a solution-oriented approach, with the ability to look beyond predefined specifications, identify opportunities, challenge assumptions constructively and propose innovative AI-driven solutions.

Collaboration & Communication: Strong communication and stakeholder engagement skills, with the ability to collaborate effectively across onshore and offshore engineering teams, contribute to open architectural discussions and translate business requirements into scalable technical solutions.

Career Experience: Approximately 5+ years of commercial software or data engineering experience within complex enterprise environments, including 2+ years of hands-on experience building, deploying and maintaining production Generative AI/LLM applications, RAG pipelines or autonomous agent solutions.

What you'll experience

• Be part of Australia's largest retailer and contribute to its growing technology and AI capabilities in India.
• Opportunity to work on next-generation Agentic AI, Generative AI and enterprise intelligent automation solutions.
• Be part of an integrated, collaborative Applied AI team working across India and Australia.
• Direct exposure to onshore Platform Managers, Architects, engineering leaders and business stakeholders.
• Opportunity to influence technical design, product discovery and the evolution of enterprise AI capabilities.
• Work with emerging AI technologies, cloud-native platforms and large-scale enterprise data ecosystems.
• Contribute to building reusable, governed AI assets that deliver meaningful business outcomes.
• Continuous technical learning, mentoring and opportunities for professional growth and career development.
• A flexible approach to work.

Everyone belongs at Woolworths Group

Diversity, equity, inclusion, and belonging are key to realising our purpose of better together for a better tomorrow. We recognise the value our team's diversity brings to our business, customers, and communities and that teams with diverse experiences and backgrounds enrich our group and are better able to innovate and solve problems.

As one of the largest employers in Australia and New Zealand, we aim to create a truly inclusive workplace where everyone feels that they belong, can be their best selves, and reach their full potential.

We encourage all candidates to apply; please let us know in your application if we can support you with any adjustments in the hiring process.

Your Personal Data

By submitting your application, you acknowledge and consent to Zinnov Management Consulting Private Limited and its subsidiaries (Zinnov) and/or Woolworths Group Limited and its subsidiaries (Woolworths Group) collecting, processing and disclosing your personal information, including any sensitive personal information provided by you, for the purposes of managing the recruitment process, assessing your suitability for employment, communicating with you regarding your application, and, where appropriate, considering you for future employment opportunities, to the extent relevant.

If your application is successful, Zinnov and/or Woolworths Group will also use your personal information, including sensitive personal information, for managing your ongoing working relationship.

Your personal information will be handled in accordance with applicable privacy laws.

To learn more about how we collect, use, disclose and safeguard your personal information, including your privacy rights, please refer to the Zinnov Privacy Policy and Woolworths Group Team Member Privacy Notice.