Role & Responsibilities
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).
Skills: artificial intelligence,integration,platforms,boot,aws,enterprise,java,cloud,spring,azure
