Job Description
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 AI
platform solutioning, AIOps, or MLOps roles
Role Overview
We are seeking a Senior Solution Consultant to
strengthen 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, AI
product solutioning, and operationalization of AI models in enterprise
communication environments. The candidate will work closely with presales,
product, engineering, and delivery teams to design scalable, reliable, and
production-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.
Mandatory Skills & Experience (Shortlisting Criteria)
Core Technical Skills
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
