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Tier-1 brand, generalist senior title, metro location, and mid-level experience increase applicant competition.
Role requires specific backend, cloud, and ML expertise making cross-industry transitions difficult.
Explicit 4+ years requirement plus mandatory Java, ML, Kafka, cloud, and DevSecOps skills increases screening strictness.
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Lead moderately complex technical initiatives including design, coding, testing, debugging, and documentation within software engineering projects.
Develop and integrate AI/ML models (LLMs, NLP, embeddings, RAG pipelines) and Java microservices into scalable, production-ready capabilities.
Oversee cloud-native solutions and DevSecOps practices including CI/CD pipelines, monitoring, and ensuring performance and security of APIs and microservices.
Minimum 4+ years of software engineering experience or equivalent experience/training.
Proficiency in AI/ML technologies such as LLMs, NLP, PyTorch, TensorFlow, ML.NET, Azure AI, OpenAI APIs.
Proficiency in Java 11+/17, Spring Boot, Kafka, and microservice design principles.
Experience with cloud platforms (Azure/AWS/GCP), DevOps, CI/CD, and observability tools like Splunk or Grafana.
Experienced in building and deploying AI-powered business workflows with measurable success criteria and scalable performance.
Skilled in event streaming architectures and high performance Java microservices development with security and fault tolerance.
Proficient in cloud-native development, DevSecOps enforcement, and observability implementation in enterprise environments.