Minimum 8 years of overall experience in software engineering, application development, integration, and SDLC delivery.
Strong recent hands-on software development experience; candidate must be comfortable spending majority of time coding, debugging, designing, and delivering working software.
Minimum 8 years of hands-on Java backend development experience, including Spring Boot, REST APIs, microservices, and open-source technologies.
Minimum 3 years of hands-on experience with event-driven systems, messaging, streaming, integration, or notification platform capabilities.
Hands-on experience with Apache Camel or equivalent enterprise integration frameworks.
Minimum 4 years of hands-on experience with AWS or equivalent cloud services such as EC2, S3, RDS, VPC, CloudFront, Lambda, EKS, ECS, API Gateway, DynamoDB, DocumentDB, AmazonMQ, or related services.
Strong hands-on AI/GenAI implementation experience in enterprise or production-grade applications; AI experience should not be limited to strategy, vendor discussions, or conceptual understanding.
Practical experience involves personally implementing one or more AI capabilities such as LLM integration, prompt engineering, RAG, embeddings/vector search, semantic search, classification, summarization, AI-assisted workflow automation, or decision-support capabilities.
Understanding responsible AI and secure AI engineering practices, including data privacy, access control, guardrails, evaluation, monitoring, hallucination risk, human review where needed, and auditability.
Experience with observability and analytics tools such as Dynatrace, ELK Stack, CloudWatch, or equivalent tools.
Experience working in agile delivery environments where CI/CD, automated testing, code quality, deployment readiness, and production support are critical.
Demonstrated knowledge of software engineering best practices such as version control, software packaging, release management, automated testing, secure coding, and operational readiness.
Strong analytical and problem-solving skills with ability to diagnose complex technical issues independently.
Must be self-motivated, collaborative, and able to communicate effectively with technical and non-technical stakeholders.
What will help you propel from the pack (Preferred Qualifications):
Experience designing and developing enterprise notification, communication, customer messaging, content management, or eventing platform solutions.
Experience with Twilio or similar communication/messaging platforms.
Experience applying AI to communication use cases such as personalization, routing, prioritization, content quality checks, template assistance, intent classification, summarization, or operational anomaly detection.
Experience with AI observability, LLMOps/MLOps practices, model/prompt evaluation, AI guardrails, and production monitoring of AI-enabled features.
AWS certification or equivalent cloud certification.
Experience in high-scale, 24x7 production environments.
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