Solutions Architect - AI/ML

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.