Description :

We're seeking an experienced Team Lead AI & DevOps to drive our global headquarters' AI and automation initiatives from Pune.

You'll lead a cross-functional team of AI/ML and DevOps engineers, delivering production-grade solutions for worldwide deployment while building technical capabilities and mentoring talent locally.

Key Responsibilities :

Leadership & Coordination :

- Lead and mentor a team of AI/ML Engineers and DevOps Engineers in Pune.

- Coordinate development activities with global headquarters projects and international stakeholders.

- Act as technical bridge between Pune engineering team and global product/architecture teams.

- Foster a culture of innovation, continuous learning, and knowledge sharing.

- Develop talent through coaching, skill-building initiatives, and career path planning.

Technical Ownership :

- Architect and oversee scalable AI/ML solutions (GenAI, LLMs, traditional ML) from concept to production.

- Design and implement robust MLOps pipelines, CI/CD workflows, and infrastructure automation for local, cloud, and hybrid deployments.

- Ensure production-grade quality : monitoring, security, reliability, and performance optimization across deployment models.

- Drive technical standards and best practices across AI and DevOps domains.

- Translate global headquarters requirements into technical solutions aligned with enterprise architecture.

Strategic Contribution :

- Collaborate with Head of Digital on AI and automation strategy for headquarters projects.

- Identify opportunities for AI-driven innovation and operational efficiency.

- Contribute to technology roadmaps and investment decisions.

- Represent Pune engineering capabilities in global forums and architecture reviews.

What You Bring :

Experience & Technical Depth :

- 8+ years in software engineering, with 4+ years in AI/ML and 3+ years in DevOps/infrastructure.

- Proven team leadership : Managed cross-functional engineering teams (minimum 3-5 people).

- GenAI/LLM expertise : Production experience with LLMs, RAG architectures, prompt engineering, vector databases.

- MLOps mastery : End-to-end ML pipelines, model deployment, monitoring, and lifecycle management.

- Hybrid deployment experience : Strong expertise in on-premises, cloud, and hybrid infrastructure (not cloud-only).

- DevOps proficiency : Kubernetes, Docker, CI/CD (GitHub Actions/Jenkins/GitLab), infrastructure-as-code (Terraform/Ansible).

- Cloud & on-prem : Experience with AWS/Azure/GCP and on-premises systems, edge computing, or air-gapped environments.

- Programming : Strong Python; familiarity with Java, Go, or similar languages.

Leadership & Collaboration :

- Demonstrated ability to mentor engineers and grow technical talent.

- Experience working in global, distributed teams across time zones on headquarters-level projects.

- Excellent stakeholder management and communication skills (technical and non-technical audiences).

- Track record of delivering complex projects on time with cross-functional dependencies.

- Comfortable navigating ambiguity and driving initiatives independently.

Mindset & Culture Fit :

- Pioneering spirit : Passionate about emerging AI technologies and automation.

- Customer-centric : Understand AI solutions through the lens of business value.

- Collaborative : Thrive in matrix organizations with lateral coordination.

- Pragmatic innovator : Balance cutting-edge exploration with production reliability.

What We Offer :

- Global impact : Work on headquarters-level projects with international visibility.

- Talent development mandate : Shape and grow a high-performing engineering team.

- Strategic influence : Direct collaboration with Head of Digital and global technical leadership.

- Innovation space : Explore GenAI, automation, and next-generation technologies in diverse deployment scenarios.

- Competitive package : Aligned with senior technical leadership roles in Pune.

Preferred Qualifications :

- Bachelor's/Master's in Computer Science, Engineering, or related field.

- Publications, patents, or open-source contributions in AI/ML.

- Certifications : AWS/Azure/GCP Professional, Kubernetes (CKA/CKAD), or AI/ML specializations.

- Experience in manufacturing, industrial automation, or B2B technology is a plus.

- Familiarity with edge computing, IoT platforms, or industrial deployment environments.