Ishan Technologies - Technical/Solution Architect - AI/ML Solution

Role Overview :

The Technical Solution Architect (AI/ML) will be responsible for designing, architecting, and delivering scalable AI/ML solutions for telecom use cases. This role will work closely with business stakeholders, data scientists, engineering teams, and telecom domain experts to translate business problems into robust AI-driven solutions that drive operational efficiency, customer experience, and revenue growth.

Key Responsibilities :

- Design end-to-end AI/ML solution architectures covering data ingestion, feature engineering, model development, deployment, monitoring, and lifecycle management.

- Define scalable, secure, and high-performance architectures for machine learning and deep learning workloads.

- Select appropriate AI/ML frameworks, tools, and platforms (open-source and cloud-native).

Architect AI/ML solutions for telecom use cases such as :

- Network optimization and fault prediction

- Predictive maintenance of network infrastructure

- Customer churn prediction and retention

- Revenue assurance and fraud detection

- Personalized offers and recommendation engines

- Call Detail Record (CDR) analytics

- Work closely with telecom business teams to understand domain-specific challenges and translate them into AI-driven solutions.

- Design data pipelines for structured and unstructured telecom data (CDRs, network logs, OSS/BSS data, IoT data).

- Architect big data solutions using platforms such as Hadoop, Spark, Kafka, and real-time streaming frameworks.

- Ensure data quality, governance, security, and compliance with telecom regulations.

- Define MLOps frameworks for CI/CD of ML models including versioning, testing, deployment, monitoring, and retraining.

- Architect containerized and microservices-based ML deployments using Docker, Kubernetes, and cloud-native services.

- Ensure model explainability, performance monitoring, and bias detection in production environments.

- Architect AI/ML solutions on public cloud platforms (AWS, Azure, GCP) or hybrid/on-prem environments.

- Define cloud resource optimization strategies for AI/ML workloads.

- Ensure high availability, disaster recovery, and scalability of AI systems.

- Act as a technical advisor to business and leadership teams on AI/ML strategy and roadmap.

- Lead technical solutioning during pre-sales, RFPs, and client workshops.

- Review and approve technical designs, code standards, and best practices.

- Mentor data scientists and ML engineers on architecture, performance, and scalability.

- Ensure AI/ML solutions comply with telecom security standards, data privacy regulations, and ethical AI guidelines.

- Implement secure data access, encryption, and identity management across AI platforms.

Required Skills & Qualifications :

Technical Skills :

- Strong expertise in AI/ML algorithms including supervised, unsupervised, deep learning, NLP, and time-series modeling.

- Hands-on experience with Python, ML libraries (TensorFlow, PyTorch, Scikit-learn).

- Experience with big data and streaming technologies (Spark, Kafka, Flink).

- Strong knowledge of MLOps tools and frameworks (MLflow, Kubeflow, Airflow).

- Experience with cloud AI services (AWS SageMaker, Azure ML, GCP Vertex AI).

- Strong understanding of REST APIs, microservices, and system integration