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AI/ML Architect (Agentic AI, GenAI)
AI/ML Architect (Agentic AI, GenAI)Transnational AI Private Limited • Guntur, IN
AI / ML Architect (Agentic AI, GenAI)

AI / ML Architect (Agentic AI, GenAI)

Transnational AI Private Limited • Guntur, IN
5 days ago
Job description

About the Company

Transnational AI Private Limited is a deep-tech organization building intelligent digital platforms that combine modern event-driven architecture, cloud-native systems, and AI / ML-powered intelligence.

Job Role

We are hiring a senior Technical Architect to design and lead the backend development and system design for real-time, event-driven microservices that seamlessly integrate AI / ML capabilities. You will work with cutting-edge frameworks such as FastAPI, Kafka, AWS Lambda, and collaborate with data scientists to embed ML models into production-grade systems.

Responsibilities

System Architecture & Event-Driven Design

  • Design and implement event-driven architectures using Apache Kafka to orchestrate distributed microservices and streaming pipelines.
  • Define scalable message schemas (e.g., JSON / Avro), data contracts, and versioning strategies to support AI-powered services.
  • Architect hybrid event + request-response systems to balance real-time streaming and synchronous business logic.

Backend & AI / ML Integration

  • Develop Python-based microservices using FastAPI, enabling both standard business logic and AI / ML model inference endpoints.
  • Collaborate with AI / ML teams to operationalize ML models (e.g., classification, recommendation, anomaly detection) via REST APIs, batch processors, or event consumers.
  • Integrate model-serving platforms such as SageMaker, MLflow, or custom Flask / ONNX-based services.
  • Cloud-Native & Serverless Deployment (AWS)

  • Design and deploy cloud-native applications using AWS Lambda, API Gateway, S3, CloudWatch, and optionally SageMaker or Fargate.
  • Build AI / ML-aware pipelines that automate retraining, inference triggers, or model selection based on data events.
  • Implement autoscaling, monitoring, and alerting for high-throughput AI services in production.
  • Data Engineering & Database Integration

  • Ingest and manage high-volume structured and unstructured data across MySQL, PostgreSQL, and MongoDB.
  • Enable AI / ML feedback loops by capturing usage signals, predictions, and outcomes via event streaming.
  • Support data versioning, feature store integration, and caching strategies for efficient ML model input handling.
  • Testing, Monitoring & Documentation

  • Write unit, integration, and end-to-end tests for both standard services and AI / ML pipelines.
  • Implement tracing and observability for AI / ML inference latency, success / failure rates, and data drift.
  • Document ML integration patterns, input / output schema, service contracts, and fallback logic for AI systems.
  • Qualification & Skills

  • 10+ years of backend software development experience with 4+ years in AI / ML integration or MLOps.
  • Strong experience in productionizing ML models for classification, regression, or NLP use cases.
  • Experience with streaming data pipelines and real-time decision systems.
  • AWS Certifications (Developer Associate, Machine Learning Specialty) are a plus.
  • Exposure to data versioning tools (e.g., DVC), feature stores, or vector databases is advantageous.
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