AI/ML Backend Engineer (Java)

Hiring for a Client - Kanerika About the Role: We are seeking strong Senior Java + AI Platform Engineers to work on strategic enterprise initiatives focused on building scalable AI Governance, Observability, and Compliance platforms. The ideal candidate will have strong expertise in Java backend engineering, distributed systems, AI integrations, telemetry pipelines, and cloud-native architectures. This role involves designing scalable enterprise-grade platforms capable of monitoring, governing, and securing AI interactions across large-scale enterprise environments.

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 Strong Senior AI Java Engineer profile (Java + Spring Boot / Hands-on AI Platform Integration) Mandatory (Experience 1)- 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) Mandatory (Experience 2) - 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. Mandatory (Experience 3) – Must have proven experience building SaaS / cloud-native applications with strong REST API and microservices architecture expertise. Mandatory (Experience 4) – Must have strong SDLC and quality engineering discipline — unit/integration testing and CI/CD (GitHub Actions, Jenkins or similar).

Mandatory (Experience 6) – Must have experience with event streaming / event-driven architecture (Kafka, Kinesis, Event Hub or Pub/Sub). Preferred (Experience)- 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).