16 hours ago
Bengaluru, IndiaMid Level / Senior
Responsibilities
- Architect, build, deploy, monitor, and optimize production-grade AI products and AI/ML platforms.
- Develop generative AI applications, prompt architectures, RAG pipelines, and fine-tuned models.
- Design intelligent systems for legacy code parsing, translation, modernization, and technical document generation.
- Build resilient, serverless AI microservices and batch-processing pipelines on Google Cloud Platform.
- Establish CI/CD pipelines, automated testing frameworks, API designs, documentation, and engineering best practices for AI assets.
- Implement AI FinOps capabilities including tagging, billing telemetry, token metering, cost attribution, model routing, and inference-cost optimization.
- Collaborate with Product Managers, UX Designers, Software Architects, and domain experts on requirements and enterprise integration.
- Mentor junior team members and promote production ML engineering practices.
Requirements
- Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, Software Engineering, or a related quantitative field.
- At least one recognized cloud or AI certification, such as Google Cloud Professional Machine Learning Engineer or an equivalent advanced credential.
- 4–7 years of hands-on experience building, deploying, and scaling end-to-end AI/ML products, generative AI applications, code transformation tools, and intelligent software automation systems.
- Extensive experience with Google Cloud Platform, including Vertex AI, Cloud Run, BigQuery, Cloud Functions, and GKE.
- Strong proficiency with LLMs, RAG architectures, vector databases, and frameworks such as LangChain or LlamaIndex.
- Mastery of Python and solid proficiency with modern web and backend stacks, API development, gRPC, and microservice design.
- Familiarity with abstract syntax trees, static code analysis, compiler concepts, and domain-specific language translation.
- Experience with MLOps workflows, model tracking, automated testing, Docker, Kubernetes, and CI/CD pipelines.
- Experience with token metering, cost attribution, model routing, OpenTelemetry, and Cloud Monitoring.
- Preferred experience includes source-to-source compilers, automated code conversion, design document generation, legacy enterprise frameworks, quantitative product analytics, or an AI-focused GitHub portfolio.
Benefits
- Permanent employment with Airbus India Private Limited.
- Flexible working arrangements are supported where possible to enable easier collaboration and innovation.