
Artificial Intelligence Architect
3 weeks ago
Key Responsibilities :
- Implement cloud migration strategies for monolithic systems to microservices/serverless architectures using AWS, Azure, and GCP.
- Lead development of document automation systems leveraging models such as BART, LayoutLM, and Agentic AI workflows.
- Architect and optimize data lakes, ETL pipelines, and analytics dashboards using Databricks, PySpark, Kibana, and MLOps tools.
- Build centralized search engines using ElasticSearch, Solr, and Neo4j for intelligent content discovery and sentiment analysis.
- Ensure application and ML pipeline security with tools like OWASP ZAP, SonarQube, WebInspect, and container security tools.
- Collaborate with InfoSec and DevOps teams to maintain CI/CD pipelines, perform vulnerability analysis, and ensure compliance.
- Guide modernization initiatives across app stacks and coordinate BCDR-compliant infrastructures for mission-critical services.
- Provide technical leadership and mentoring to engineering teams during all phases of the Skills & Qualifications :
- 12+ years of total experience, with extensive tenure as a Solution Architect in AI and cloud-driven experience with :
- Generative AI, LLMs, Prompt Engineering, LangChain, AutoGen, Vertex AI, AWS Bedrock.
- Python, Java (Spring Boot, Spring AI), PyTorch.
- Vector & Graph Databases : ElasticSearch, Solr, Neo4j.
- Cloud Platforms : AWS, Azure, GCP (CAF, serverless, containerization).
- DevSecOps : SonarQube, OWASP, oAuth2, container security.
- Strong background in application modernization, cloud-native architecture, and MLOps
orchestration.
- Familiarity with front-end technologies : HTML, JavaScript, Angular, : (Any 2 to 3)
- Google Professional Cloud Architect.- AWS Solution Architect Associate.
- Cisco Certified Design Associate (CCDA).
- Cisco Certified Network Associate (CCNA).
- Cisco Security Ninja Green Belt.
(ref:hirist.tech)-
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