Manager - Customer Interaction Suite

Tata Communications Redefines Connectivity with Innovation and IntelligenceDriving the next level of intelligence powered by Cloud, Mobility, Internet of Things, Collaboration, Security, Media services and Network services, we at Tata Communications are envisaging a New World of Communications

Broad outline of the Role

Lead end-to-end delivery and L3 operational support for complex customer solutions, ensuring high availability, stability, and quality outcomes.

Drive solution design and prototyping based on customer requirements, while supporting pre-sales and solutioning for key deals. Collaborate with Product teams to enhance service offerings and ensure alignment with customer needs. Own critical projects, providing technical leadership, guidance, and governance to project teams to ensure successful delivery. Act as the escalation point for complex production issues, independently troubleshooting and resolving high-impact challenges. Oversee operational performance, ensuring delivery outcomes directly contribute to business objectives and SLA commitments. Mentor and guide technical teams, reviewing deliverables and ensuring adherence to standards, processes, and best practices. Drive continuous improvement by identifying gaps, optimizing processes, and enhancing tools, techniques, and methodologies.

Lead small teams or workgroups, ensuring effective collaboration and execution across delivery and operations. Demonstrate strong ownership, prioritization, and decision-making skills with minimal supervision. Graduate in Engineering Experience 5 10 years

Minimum Qualifications & Experience

• Bachelor s degree in engineering 5-10 Years relevant experience

  Key Responsibilities

  AI Delivery & Customer Enablement

  • Lead end-to-end delivery of AI-driven CX solutions (LLM-based bots, Voice AI, chat, and omnichannel platforms) from design to production rollout.
  • Work closely with customers to understand business requirements and translate them into scalable AI/LLM architectures and workflows.
  • Ensure successful implementation of AI use cases including conversational bots, RAG pipelines, automation workflows, and customer journey orchestration.
  • Oversee integration of AI services with enterprise systems via APIs, middleware, and channel platforms (voice/SIP, WhatsApp, chat, email).
  • Drive model validation, prompt optimization, and performance tuning to improve AI accuracy, response quality, and customer experience.
  • Ensure production readiness of AI deployments, including scalability, monitoring, failover, and compliance with security and governance standards.
  • Act as a technical escalation point for customer issues related to AI solutions, ensuring timely resolution and stakeholder communication.
  • Collaborate with Product, Engineering, and Data teams to continuously enhance AI capabilities and align with customer expectations.
  • Enable customers and internal teams through knowledge transfer, solution documentation, and best practices for AI operations and lifecycle management.
  • Track delivery KPIs including adoption, accuracy, latency, and customer satisfaction for continuous improvement.

  Operational Support & Incident Management

  • Provide Level‑2 SRE support for AI platforms, customer‑facing applications, and underlying cloud infrastructure to ensure high availability, stability, and reliability.
  • AIOps supports SRE teams by:Using machine learning to accelerate and improve RCA accuracy. Correlating logs, events, metrics for faster resolution.
  • Escalate complex, high‑impact, or systemic issues to Vendor/partner/Infra teams with complete diagnostics, logs, timelines, and business impact analysis.
  • Drive cross‑functional collaboration (CFT) with Vendor/Partner, Product, Cloud and Security Teams to ensure rapid incident resolution and service stability.

  Observability & Monitoring Management

  • SREs own the health of production systems: Monitor system performance and maintain high availability. Recover from failures and implement long-term fixes.
  • Support proactive detection of anomalies before they impact customer experience or SLAs.

  Deployment & Release Support

  • Support application deployments, patches, and upgrades across environments (QA, Pre‑Production, and Production).
  • Validate deployments and conduct post‑release health checks along with Vendor/Partner/ Developer/QA to ensure platform stability.
  • Ensure deployment activities adhere to change management, release governance, and SLO requirements.

  Platform & Infrastructure Operations

  • Provide operational support for AI/ML platforms, APIs, databases, middleware, and integration services in production.
  • Manage configuration changes, environment variables, secrets, and access controls following security and compliance standards.
  • Work with cloud platforms (AWS / Azure / Vayu Cloud) and containerized environments (Docker / Kubernetes) to support scalable and resilient operations.

  Collaboration & Communication

  • SREs collaborate closely with developers by: Identifying software issues impacting reliability. Participating in design for reliability, scalability, and performance.
  • Work closely with technical support teams, DevOps, AI developers, Technical Project manager (TPM), infrastructure teams, and vendors/partners.
  • Lead shift handovers, operational reviews, and daily/weekly health calls, ensuring no gaps in process adherence or customer SLAs.

  Documentation & Continuous Improvement

  • Create and maintain runbooks, SOPs, knowledge articles, and operational documentation.
  • Identify and propose automation opportunities to reduce manual effort and improve incident response times.
  • Contribute to continuous reliability improvements through: Runbook enhancements, Alert tuning, Automation and tooling, Operational best practices
  • Actively participate in post‑incident reviews and service optimization initiatives.

  Core Knowledge & Skills

  • AI / LLM & CX Technologies
  • LLM platforms (Azure OpenAI, OpenAI, Claude, Gemini, Bedrock)
  • Prompt engineering & AI response validation
  • Voice AI, Chatbots, NLP, STT/TTS
  • RAG pipelines, AI orchestration, guardrails (Ragas / DeepEval)
  • Omnichannel CX platforms (voice, SIP, WhatsApp, chat, email)
  • Cloud & Infrastructure

  o AWS / Azure cloud platforms

  o High availability, scalability, DR/BCP

  o IAM, configuration & secrets management

  • Containers & Platform
  • Docker, Kubernetes (K8s)
  • Environment management (QA/Prod)
  • Systems & Scripting
  • Linux/Unix administration
  • Shell scripting
  • Python (FastAPI, automation)
  • API & Integration
  • REST / gRPC APIs
  • Webhooks, middleware integrations
  • API debugging tools (Postman)
  • Observability & Monitoring
  • Prometheus, Grafana, New Relic
  • CloudWatch (AWS)
  • Databases
  • MySQL, PostgreSQL
  • Query optimization, indexing, performance tuning

  Tools

  • CI/CD (Jenkins, GitLab, Azure DevOps)
  • Git version control
  • VS Code (development/debugging)

  Telecom / Voice (Optional but strong)

  • Asterisk, FreeSWITCH, Kamailio
  • SIP/VoIP fundamentals