Job Description: AI Solution Architect
Location: Hyderabad
Work Mode: Hyd 5 days Office
Experience: 12+ years
Position Overview:
We are seeking an experienced AI Solution Architect to lead the design and implementation of AI-driven, cloud-native applications.
The ideal candidate will possess deep expertise in Generative AI, Agentic AI, cloud platforms (AWS, Azure, GCP), and modern data engineering practices.
This role involves collaborating with cross-functional teams to deliver scalable, secure, and intelligent solutions in a fast-paced, innovation-driven environment.
Key Responsibilities:
- Design and architect AI/ML solutions, including Generative AI, Retrieval-Augmented Generation (RAG), and fine-tuning of Large Language Models (LLMs) using frameworks like LangChain, LangGraph, and Hugging Face.
- 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 SDLC.
Required Skills & Qualifications:
- 12+ years of total experience, with extensive tenure as a Solution Architect in AI and cloud-driven transformations.
Hands-on 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, JQuery.