Tata Communications
Manager - Customer Interaction Suite

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About The Company
Tata Communications Redefines Connectivity with Innovation and Intelligence
Driving 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
Job Description
The Technical Program Manager (TPM) plays a critical role in the successful delivery of customer onboarding, technical projects, and AI-powered solutions.
The TPM is responsible for managing end-to-end program execution across customer, engineering, product, and operations teams, ensuring projects are delivered on time, within budget, and according to agreed business outcomes.
This is an operational role which combines traditional program and delivery management capabilities with hands-on knowledge of emerging AI technologies, including Generative AI, Agentic AI frameworks, Prompt Engineering, RAG architectures, workflow orchestration, AI testing, and production deployment.
The ideal candidate can bridge business requirements and technical implementation while driving operational excellence throughout the project lifecycle.
Key Responsibilities
Program & Project Management
- Manage project initiation, planning, scheduling, execution, monitoring, and closure using established project management methodologies and governance frameworks.
- Develop and maintain project plans, milestones, dependencies, resource allocation, and delivery schedules.
- Track project performance against scope, timeline, budget, and quality metrics.
- Provide regular project status reporting to customers, stakeholders, and leadership teams.
- Manage project risks, issues, assumptions, and dependencies while driving mitigation and resolution plans.
- Lead customer, partner, vendor, and internal stakeholder meetings to ensure alignment and successful delivery.
- Ensure customer requirements are documented, validated, and translated into actionable implementation plans.
- Drive continuous improvement of project management methodologies, tools, templates, and delivery processes.
Reasons to use Rodeo
I’m in my final year doing Economics and I don’t know whether to apply for grad schemes now or do a masters first. What do you think?
Honest answer — it depends on where you want to end up. A lot of top grad schemes (Big 4, civil service, banking) don’t need a masters. Let’s look at the ones you’d be competitive for now, and we can decide if a masters actually adds anything.
Also worth knowing: most autumn 2026 applications are open now. Timing matters more than you think.
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Graduate Consultant — 2026 Scheme
Why you're a good match
StrongYour economics background and your summer at a regional bank line up with what PwC looks for on the consulting scheme. Applications close in four weeks.
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Why you're a good match
You’ve got the grades and the economics background, and your bank internship is exactly the experience this scheme looks for. Apply soon — deadlines close within the month.
Experience fit
Your summer at the bank plus your econometrics coursework map directly to the day-one responsibilities on this scheme — client modelling, market briefings, and deal support.
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Technical Delivery
- Collaborate with Product, Engineering, Solution Architects, and other teams in Operations to assess solution feasibility and implementation approaches.
- Oversee delivery activities involving APIs, authentication mechanisms, networking, cloud services, integrations, and workflow automation.
- Facilitate troubleshooting, issue resolution, and escalation management during implementation and operational phases, as in day by day relation with the customer.
- Ensure technical solutions meet customer expectations and business objectives.
AI Program Management & Delivery


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- Lead end-to-end delivery of Agentic AI and Voice AI initiatives, from discovery and requirements gathering through deployment and post-production optimization.
- Manage AI solution design activities, including workflow definition, conversational journeys, intent modeling, multilingual experiences, and NLP training requirements.
- Coordinate development and deployment of Agentic AI solutions leveraging RAG, MCP, orchestration frameworks, LLMs, and external integrations.
- Collaborate with AI engineers and data teams to define prompting strategies, evaluation criteria, and testing frameworks.
- Drive prompt engineering lifecycle management, including prompt design, optimization, testing, versioning, and performance measurement.
- Establish AI quality assurance practices covering functional testing, hallucination assessment, response quality, accuracy validation, safety controls, and user acceptance testing.
- Define success metrics for AI projects, including accuracy, latency, adoption, operational efficiency, and business impact.
- Monitor AI solution performance post-deployment and drive continuous improvements.
- Experience defining AI acceptance criteria, evaluation frameworks, and quality metrics for Generative AI solutions, including accuracy, relevancy, hallucination rate, safety, and user satisfaction.
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