AI Engineer

About the job

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 AI Engineer 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 • 7+ 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.

Requirements

• AI / ML integration
• FastAPI
• Kafka
• AWS Lambda
• Microservices

Qualifications

• 7+ years of backend software development experience
• 4+ years in AI / ML integration or MLOps
• Strong experience in productionizing ML models for classification
• Experience with streaming data pipelines

Preferred Technologies

• AI / ML integration
• FastAPI
• Kafka
• AWS Lambda
• Microservices

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.