We are looking for an experienced AI & Automation Lead to define, build, and scale AI-enabled automation capabilities for an enterprise labeling compliance and artwork validation platform. This strategic and hands-on leadership role will translate business, regulatory, and operational requirements into secure, scalable, explainable, and production-ready solutions.

The ideal candidate brings 10+ years of experience across enterprise technology, automation, application engineering, and AI-enabled transformation, including experience leading multidisciplinary teams and complex delivery programs. You will work closely with product owners, AI/ML engineers, architects, compliance stakeholders, business teams, and technology partners to deliver a scalable MVP and establish a future-ready automation platform.

Key Responsibilities:

- Define and own the AI and automation strategy, architecture, roadmap, and delivery model for the platform.
- Lead the design, development, testing, deployment, and scaling of AI-enabled automation solutions across frontend, backend, APIs, data, workflows, and integration layers.
- Convert business, regulatory, and compliance requirements into scalable solution designs, reusable capabilities, and measurable delivery outcomes.
- Lead multidisciplinary teams comprising AI/ML engineers, software engineers, automation developers, UX specialists, and external partners.
- Design intelligent, human-in-the-loop workflows for review, approval, exception handling, escalation, and audit-trail management.
- Guide the integration of AI/ML models, OCR, document intelligence, computer vision, rules engines, and automation services into robust and explainable business applications.
- Establish reusable APIs, modular services, orchestration patterns, and automation components that can scale across business units, markets, and use cases.
- Drive integration with enterprise systems such as document repositories, workflow platforms, product data sources, regulatory systems, reporting tools, and identity services.
- Ensure solutions meet enterprise standards for security, privacy, reliability, performance, maintainability, traceability, and compliance.
- Define governance for model usage, prompt and workflow lifecycle, access control, logging, auditability, monitoring, and responsible AI.
- Evaluate AI, automation, low-code,



and orchestration technologies and recommend fit-for-purpose platforms and engineering patterns.
- Own technical quality through architecture reviews, design governance, code reviews, testing strategy, release readiness, and production support.
- Drive DevOps, CI/CD, test automation, observability, and controlled deployment practices for MVP and production releases.
- Partner with senior business and technology stakeholders to prioritize opportunities, manage dependencies, communicate risks, and demonstrate business value.
- Mentor technical team members, strengthen engineering practices, and build organizational capability in AI and automation.

Qualifications:

- Bachelor’s or Master’s degree in Computer Science, Software Engineering, Information Systems, Artificial Intelligence, Data Science, or a related field.
- Preferably 8+ years of experience in enterprise software engineering, automation, digital platforms, or AI-enabled solution delivery.
- At least 2 years of experience in a technical leadership, solution leadership, engineering management, or architecture role.
- Proven experience leading complex, cross-functional technology initiatives from discovery and architecture through implementation and production scale-up.
- Strong understanding of AI solution patterns, generative AI, intelligent automation, workflow orchestration, and human-in-the-loop design.
- Hands-on understanding of modern application architecture, including frontend frameworks, backend services, REST APIs, microservices, event-driven patterns, and data platforms.
- Experience with Python and one or more enterprise application technologies such as Node.js, Java, or .NET.
- Experience integrating AI services and model outputs into enterprise applications in a secure, reliable, and explainable manner.
- Strong experience with cloud platforms such as Azure, AWS, or GCP and with cloud-native architecture and services.




- Experience with relational and NoSQL databases such as PostgreSQL, SQL Server, MongoDB, or similar technologies.
- Experience with CI/CD, Git-based version control, automated testing, observability, and modern software delivery practices.
- Solid knowledge of authentication, authorization, API security, secure coding, data privacy, and role-based access control.
- Demonstrated ability to influence senior stakeholders, manage competing priorities, and communicate complex technical topics clearly.
- Robust analytical, problem-solving, team leadership, and vendor-management skills.

- Preferred Qualifications
- Experience delivering workflow, compliance, regulatory, quality, or approval-based enterprise applications.
- Experience with generative AI, large language models, retrieval-augmented generation, AI agents, prompt orchestration, or responsible AI controls.
- Familiarity with OCR, document processing, computer vision, artwork validation, and structured information extraction.
- Experience with automation platforms, business process management tools, low-code platforms, or robotic process automation.
- Experience with containerization and orchestration technologies such as Docker and Kubernetes.
- Knowledge of event-driven architectures, message queues, asynchronous processing, and enterprise integration patterns.
- Experience managing technology vendors, implementation partners, budgets, delivery plans, and statements of work.
- Understanding of audit logging, traceability, validation, and regulated-process application design.
- Exposure to product lifecycle, packaging, labeling, quality, or compliance processes is an advantage.

- Key Skills

- AI and automation strategy

- Enterprise solution architecture
- Generative AI and intelligent automation
- Workflow orchestration and human-in-the-loop design
- Full stack and cloud-native application development
- API, microservices, and event-driven architecture

- Enterprise system integration
- Secure and responsible AI engineering
- DevOps, CI/CD, testing, and observability
- Technical leadership and team development
- Program delivery and vendor management

- Executive stakeholder communication
- Agile delivery and cross-functional collaboration

📌 Automation and AI Tech Lead (Bengaluru)
🏢 Naukri Assist
📍 Bengaluru