Role is open for Pan India, B'lore preferred.

As part of ClientsNext, you will play a key leadership role in driving Clients shift toward Agentic AI Solutions- autonomous, domain-specific systems that transform enterprise operations.

You will lead the release management, deployment strategy, and production rollout of Agentic AI products, including flagship offerings like the Clients AP Suite and upcoming multi-agent platforms across servicelines.

This role oversees the end-to-end release lifecycle, ensuring AI agents and supporting components are packaged, validated, deployed, and scaled seamlessly across client environments with the highest standards of security, reliability, and compliance.

Responsibilities :

Release Management :

- Own the complete release lifecycle - from planning, versioning, and packaging to rollout and post-release validation.

- Define and enforce release policies, deployment checkpoints, and quality gates for Agentic AI solutions.

- Coordinate cross-functional release calendars with product, engineering, QA, and client teams.

- Automate and optimize release pipelines to ensure consistent, predictable, and compliant deployments.

Deployment Strategy & Execution :

- Develop and execute deployment playbooks covering staging, UAT, pre-prod, and production environments.

- Lead zero-downtime release strategies, controlled rollouts, and rollback/mitigation procedures.

- Oversee multi-agent orchestration deployment and integration with enterprise systems (ERP, CRM, ticketing platforms, APIs, RPA).

- Ensure deployment artifacts, configurations, and environment setups are standardized and reusable across clients.

Testing, Validation & Quality Assurance :

- Partner with QA to define functional, regression, integration, and performance testing aligned to release cycles.

- Validate AI agent behaviors, guardrails, and outputs against accuracy KPIs before release.

- Conduct release-readiness reviews and ensure all compliance/security checks are completed.

Governance, Compliance & Security :

- Ensure release processes comply with regulatory and data privacy requirements (GDPR, HIPAA, etc.

- Implement secure deployment practices, environment hardening, and risk mitigation frameworks.

- Maintain complete documentation covering release notes, deployment guides, audit logs, and SOPs.

Post-Release Monitoring C Optimization :

- Establish monitoring, logging, observability, and alerting frameworks for deployed agentic AI solutions.

- Track performance, reliability, drift indicators, and adoption trends to recommend optimizations.

- Lead root-cause analysis and resolution for post-release issues across environments.

- Support client IT and operations teams with Tier-2/3 escalations related to deployment or agent performance.

Qualifications We Seek in You :

Minimum Qualifications :

Technical Expertise :

- Strong understanding of agentic AI architectures, orchestration frameworks, LLM integrations, and enterprise AI deployment patterns.

- Proven expertise with CI/CD tools, release automation, containerization (Docker/Kubernetes), and cloud platforms (Azure, AWS, GCP).

- Knowledge of middleware (MuleSoft, Boomi), APIs, webhooks, and enterprise integrations.

Release & Deployment Skills :

- Hands-on experience managing releases of enterprise-grade AI, SaaS, or workflow automation platforms.

- Deep understanding of environment management, version control, change management, and release governance.

- Experience in deploying complex, distributed, and highly regulated solutions at scale.

Leadership & Communication :

- Ability to influence and coordinate across engineering, product, architecture, delivery, and client teams.

- Strong stakeholder communication, risk management, and decision-making skills.

- Skilled in preparing deployment plans, user guides, and client-ready technical documentation.

Education :

- Bachelors degree in Computer Science, Information Technology, Engineering, or related technical field is required.

- Masters degree (MBA / M.Tech / MS) preferred, especially with a focus on Technology Management, AI/ML, or Software Engineering.

- Certifications in Cloud (Azure/AWS/GCP), DevOps, ITIL, or AI engineering are an added advantage.