AI/ML Backend Engineer - Java

Key Responsibilities :

• Design and build pluggable evaluator services using Java and Spring Boot

• Develop scalable SaaS/cloud-native backend services and microservices

• Integrate with AI platforms including AWS Bedrock, Azure AI Foundry, Google Vertex AI, OpenAI, and Anthropic APIs

• Build orchestration frameworks and schedulers for evaluation execution workflows

• Develop AI risk scoring systems and evaluation pipelines

• Design and implement telemetry, monitoring, and observability solutions

• Build dashboards and reporting systems for evaluation results and governance insights

• Develop integrations/connectors for cloud-native event streams and event-driven architectures

• Collaborate with cross-functional engineering teams in an Agile sprint environment

• Participate in code reviews, CI/CD setup, and quality engineering practices

• Ensure adherence to software development lifecycle and engineering best practices

Ideal Candidate :

• Must have 4+ years of experience in production-grade backend engineering experience in Java and Spring Boot, designing scalable enterprise services and microservices (development roles, not support/maintenance)

• Must have significant hands-on AI integration experience as a core part of recent work building Java services that integrate with AI platforms (AWS Bedrock, Azure OpenAI / AI Foundry, Google Vertex AI, OpenAI or Anthropic APIs) at the SDK/API level.

• Must have proven experience building SaaS / cloud-native applications with strong REST API and microservices architecture expertise.

• Must have strong SDLC and quality engineering discipline unit/integration testing and CI/CD (GitHub Actions, Jenkins or similar).

• Must have experience with event streaming / event-driven architecture (Kafka, Kinesis, Event Hub or Pub/Sub).

• Experience with AI evaluation/testing or LLM eval frameworks (RAGAS, TruLens, DeepEval), AI risk scoring, or evaluation pipelines.

Preferred (Certification) :

• Cloud certifications (AWS, Azure or GCP), and orchestration frameworks (Quartz, Spring Batch)