Salary
≈ $36k – $82k per year (Estimated)
Location
In office (Bengaluru)
Seniority
Staff · 12+ years exp
First seen by Alion on Oct 24, 2026.
Overview
Company
Impact
Profile match
OneShot is an AI messaging platform that connects sales reps with relevant prospects and discovers cross-sell and upsell opportunities from existing customers, enabling sales teams to prioritize their outreach.
We are looking for a Senior AI Architect to design and scale enterprise AI/ML platforms that bridge business needs with production-ready solutions. The role focuses on AI architecture, MLOps, model deployment, observability, and platform scalability rather than core model development.
Responsibilities:
- Design scalable AI/ML platforms, including data pipelines, model deployment, serving, and monitoring.
- Define architectures for real-time inference, recommendation systems, NLP/CV, and batch processing.
- Build cloud-native, Kubernetes-based, microservices-driven AI systems.
- Architect production-grade ML serving with A/B testing, canary releases, rollback strategies, and optimization techniques.
- Establish end-to-end MLOps practices: CI/CD, model versioning, feature stores, experiment tracking, and reproducibility.
- Implement ML observability, monitoring, alerting, and performance dashboards.
- Provide technical leadership through architecture reviews, mentoring, and AI governance.
- Evaluate emerging AI technologies including LLMs, RAG, multimodal AI, and distributed training infrastructure.
Requirements:
- 12+ years in software engineering with 6+ years in AI/ML architecture and production deployment.
- Strong experience building enterprise-scale ML platforms and distributed systems.
- Expertise in Python, PyTorch/TensorFlow, Kubernetes, Docker, MLflow/Kubeflow, Kafka, Redis, and cloud platforms (AWS/GCP/Azure).
- Deep understanding of MLOps, model serving, feature stores, monitoring, and production ML patterns.
- Experience with LLM architectures, vector databases, model optimization, and GPU-based deployments.
- Strong communication, leadership, and architectural decision-making skills.
Nice to Have:
- Experience in regulated industries (finance/healthcare).
- Knowledge of Edge AI, federated learning, NLP, CV, recommendation systems, or time-series ML.
- Master's or PhD in Computer Science, AI/ML, or a related field.
Skills
Docker, Kubeflow, Kubernetes, MLOps, MLflow, Python, feature store, microservices, model serving
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