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AI Engineer/Architect

2 weeks ago

Hyderabad, Telangana, India Transnational AI Private Limited Full time US$ 1,20,000 - US$ 2,00,000 per year

Key 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.

Preferred Qualifications


• 6+ years of backend software development experience with 2+ 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.