About The Company
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
Job Title
Senior Solution Consultant – AI Platforms (AIOps / MLOps/ Agentic AI)
Location
India (Hybrid / Remote, based on project needs)
Experience
8–12 years overall experience, with at least 3–5 years in AIplatform solutioning, AIOps, or MLOps roles
Role Overview
We are seeking a
Senior Solution Consultant
tostrengthen our presales and solutioning capabilities across
CCaaS, CPaaS,and Agentic AI-based voice and digital communication platforms
.The role will focus on
AIOps and MLOps architecture, AIproduct solutioning, and operationalization of AI models
in enterprisecommunication environments. The candidate will work closely with presales,product, engineering, and delivery teams to design scalable, reliable, andproduction-ready AI solutions.
Key Responsibilities
AI Solutioning & Architecture
- Design and articulate end-to-end AI architectures covering model development, deployment, monitoring, and lifecycle management.
- Translate business and industry use cases into AI-driven communication solutions (voice bots, digital agents, agent assist, sentiment analysis, forecasting, etc.).
- Define AI solution blueprints integrating CCaaS, CPaaS, and Agentic AI platforms.
AIOps & MLOps
- Design and implement AIOps frameworks for proactive monitoring, anomaly detection, root cause analysis, and auto-remediation in large-scale communication platforms.
- Architect MLOps pipelines covering data ingestion, feature engineering, model training, CI/CD, deployment, monitoring, and retraining.
- Define governance models for model versioning, drift detection, explainability, and compliance.
Presales & Customer Engagement
- Act as a technical lead in presales engagements, supporting RFPs, solution workshops, and executive-level discussions.
- Develop solution artifacts such as architecture diagrams, solution narratives, and effort estimations.
- Collaborate with sales and product teams to shape proposals and differentiate AI-led offerings.
Cross-Functional Collaboration
- Work with CCaaS and CPaaS solution teams to embed AI capabilities into existing and new offerings.
- Provide technical mentorship to solution consultants and architects on AI operations and lifecycle management.
- Interface with engineering and delivery teams to ensure solution feasibility and smooth handover.
Core Technical Skills
Mandatory Skills & Experience (Shortlisting Criteria)
- Strong hands-on or solutioning experience in AIOps and/or MLOps.
- Experience designing and operationalizing machine learning models in production environments.
- Knowledge of ML lifecycle tools such as MLflow, Kubeflow, SageMaker, Vertex AI, Azure ML, or similar platforms is desirable
- Experience with monitoring, observability, and automation tools for AI and distributed systems is desirable
AI & Data
- Solid understanding of ML concepts (supervised/unsupervised learning, NLP, speech analytics, LLMs, model evaluation).
- Experience working with AI products (not just experimentation), including scaling, reliability, and cost optimization.
- Familiarity with LLM-based architectures, prompt engineering, RAG patterns, and AI agent frameworks is highly desirable.
Presales & Consulting
- Proven experience in solution consulting or presales roles.
- Ability to communicate complex AI concepts to non-technical and executive stakeholders.
- Experience working across multiple industries such as BFSI, Healthcare, Telecom, Retail, or Manufacturing is a plus.
Preferred / Good-to-Have Skills
Cloud & Platform
- Strong experience with at least one major cloud platform: AWS, Azure, or GCP.
- Knowledge of containers and orchestration (Docker, Kubernetes).
- Experience with APIs, microservices, and event-driven architectures.
- Exposure to voice AI, conversational AI, speech-to-text, text-to-speech, or agent assist solutions.
- Experience building or solutioning Agentic AI systems.
- Experience in CCaaS or CPaaS platforms (e.g., contact center platforms, voice, messaging, omnichannel).
- Understanding of data privacy, security, and regulatory considerations for AI systems.
Educational Qualifications
- Bachelor’s degree in Engineering, Computer Science, or a related field.
- Master’s degree or AI/ML certifications are an added advantage.
Key Attributes
- Strong analytical and system-thinking mindset
- Customer-focused, consultative approach
- Ability to operate in ambiguous, multi-product environments
- Strong documentation and presentation skills
