Bengaluru | 09/Jul/2026

About the job

We are looking for a highly experienced AI Tech Lead to architect, design, and deliver enterprise-grade Artificial Intelligence solutions for our global customers. This role is ideal for someone who combines deep technical expertise in AI, Machine Learning, and Generative AI with strong solution architecture capabilities. As an Individual Contributor, you will lead the technical implementation of AI initiatives while collaborating with cross-functional teams across onshore and offshore locations. You will be responsible for defining AI architecture, establishing engineering best practices, mentoring technical teams, and ensuring the successful delivery of scalable, secure, and production-ready AI applications. If you are passionate about building next-generation AI systems, multi-agent architectures, and cloud-native AI platforms, we'd love to hear from you.

Responsibilties

- AI Solution Architecture: Design and architect enterprise-scale AI and Generative AI solutions.
- Define AI reference architectures, engineering standards, and technology roadmaps.
- Translate business requirements into scalable AI-driven technical solutions. Evaluate and recommend appropriate AI technologies, models, and frameworks.
- AI Application Development: Design and develop end-to-end AI applications using commercial and open-source AI technologies. Build intelligent multi-agent systems using modern Agentic AI frameworks. Develop reusable AI components, services, SDKs, and frameworks. Design scalable REST APIs and Microservices for AI applications.
- AI Platform Engineering: Design scalable AI infrastructure for model training, deployment, and monitoring. Build automated CI/CD pipelines for AI applications. Implement model monitoring, logging, observability,



and performance evaluation frameworks.
- Establish best practices for AI application lifecycle management. Cloud & Infrastructure: Design and deploy cloud-native AI applications using: AWS Microsoft Azure Google Cloud Platform Implement Docker Kubernetes.
- Infrastructure as Code (Terraform & CloudFormation): Build highly available, secure, and scalable AI platforms following cloud best practices.
- Technical Leadership: Lead AI implementation across distributed engineering teams, Mentor developers and conduct architecture reviews.
- Define coding standards, design principles, and engineering best practices.
- Drive technical discussions and innovation initiatives. Project Delivery: Manage technical planning, execution, and delivery of AI initiatives Collaborate with Product Owners Architects Project Managers and Business Stakeholders Identify project risks and define mitigation strategies Ensure timely delivery of high-quality AI solutions..

Required Qualification

- Bachelor's or master's degree in computer science, Information Technology, Engineering, Artificial Intelligence, or a related field.
- 10+ years of experience in Software Engineering, Artificial Intelligence, Machine Learning, or related domains.
- Proven experience delivering enterprise-scale AI solutions in production environments.
- Robust understanding of software architecture, cloud-native application development, and distributed systems.
- Excellent analytical, problem-solving, and communication skills.
- Experience working with globally distributed teams and US stakeholders..

Skills

AI & Machine Learning.

Agentic AI.

Cloud Platforms.

DevOps & Platform Engineering.

Databases.

Integration Technologies.

LLM Engineering.

MLOps & LLMOps.

Monitoring & Observability.

Bengaluru, Hybrid | Contract

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