Solution Architect GenAI / Agentic AI

Experience: 10+ Years

Location: PAN India

Employment Type: Full-Time

Work Mode: Hybrid

Job Overview

We are looking for an experienced Solution Architect GenAI / Agentic AI with 10+ years of overall IT experience and strong expertise in solution architecture, Java, Spring Boot, Python, cloud-native technologies, and modern AI architectures.

The ideal candidate will have hands-on experience designing and implementing Generative AI and Agentic AI solutions, including LLM-based applications, RAG architectures, AI agents, prompt engineering, vector databases, and enterprise AI integrations.

The candidate should be capable of translating business requirements into scalable, secure, and production-ready technology architectures while providing technical leadership to engineering teams.

Key Responsibilities

- Define and design end-to-end solution architectures for enterprise applications and AI-powered platforms.
- Architect and implement GenAI and Agentic AI solutions using up-to-date AI frameworks and technologies.
- Design LLM-powered applications incorporating RAG, prompt engineering, vector databases, AI agents, and enterprise data sources.
- Evaluate and select appropriate AI models, frameworks, platforms, and architectural approaches based on business requirements.
- Provide technical leadership across Java, Spring Boot, Python, cloud, microservices, and AI engineering.
- Design scalable and resilient cloud-native architectures on GCP, Azure, or AWS.
- Define microservices-based architectures and integrations using REST APIs and event-driven patterns.
- Guide development teams on architecture, design principles, coding standards, performance, scalability, and security.
- Design and oversee deployment architectures using Docker, Kubernetes, and CI/CD pipelines.
- Establish best practices for integrating AI capabilities into existing enterprise applications and platforms.
- Address AI-specific considerations including security, governance, privacy, explainability, responsible AI, and model risk.
- Conduct architecture reviews, technology evaluations, and proof-of-concepts for emerging AI technologies.
- Collaborate with business stakeholders, product managers, engineering teams, data teams,



and security teams.
- Identify technical risks, define mitigation strategies, and ensure solutions meet enterprise architecture standards.

Mandatory Technical Skills

Solution Architecture

- 10+ years of overall IT experience with significant experience in Solution Architecture / Technical Architecture.
- Strong experience designing scalable, highly available, secure, and maintainable enterprise solutions.
- Ability to create architecture diagrams, technical designs, integration patterns, and technology roadmaps.
- Strong understanding of architecture principles, design patterns, scalability, performance, and resilience.

Java / Spring Boot / Python

- Solid hands-on expertise in Java.
- Strong experience with Spring Boot and developing enterprise-grade applications.
- Strong programming experience in Python, particularly for AI/ML and GenAI integrations.
- Experience integrating AI capabilities with existing Java/Python enterprise applications.

GenAI / Agentic AI

Hands-on experience with one or more modern GenAI / Agentic AI frameworks, such as:

- LangChain
- LangGraph
- CrewAI
- AutoGen
- Semantic Kernel

Strong understanding of:

- Generative AI architectures
- Agentic AI
- AI agents and multi-agent systems
- Tool/function calling
- Agent orchestration
- Memory and context management
- AI workflow orchestration
- LLM application architecture

LLM & RAG

Strong hands-on knowledge of:

- Large Language Models (LLMs)
- Retrieval-Augmented Generation (RAG)
- Prompt Engineering
- Embeddings
- Vector Search
- Vector Databases
- Context management
- AI/LLM integrations
- Model/API integration
- LLM evaluation and optimization

Experience with vector databases such as Pinecone, FAISS, Chroma, Qdrant, Weaviate, Milvus, or equivalent is desirable.

Cloud & Cloud-Native Architecture

Strong experience with at least one major cloud platform:





- Google Cloud Platform (GCP)
- Microsoft Azure
- Amazon Web Services (AWS)

Good understanding of:

- Cloud-native application architecture
- Containers and container orchestration
- Serverless technologies
- Cloud security
- IAM
- Networking
- Scalability and high availability
- Monitoring and observability

Microservices & DevOps

Strong experience with:

- Microservices architecture
- REST APIs
- API Gateway
- Docker
- Kubernetes
- CI/CD
- Git-based development
- Automated build and deployment pipelines
- Application monitoring and logging

AI Governance & Security

The candidate should have a strong understanding of enterprise AI governance and responsible AI principles, including:

- AI security
- Data privacy and protection
- Responsible AI
- AI governance frameworks
- Model risk management
- Prompt injection and AI-specific security risks
- Data leakage prevention
- Access control
- Auditability and traceability
- Model monitoring and evaluation
- Ethical and responsible use of AI

Preferred / Good-to-Have Skills

- Experience with enterprise GenAI transformation initiatives.
- Experience building production-grade Agentic AI platforms.
- Exposure to Azure OpenAI, AWS Bedrock, Google Vertex AI, or equivalent AI platforms.
- Experience with LLMs such as GPT, Claude, Gemini, Llama, or equivalent.
- Knowledge of enterprise integration patterns and event-driven architecture.
- Experience with Kafka or other messaging platforms.
- Knowledge of SQL/NoSQL databases.
- Experience with observability and AI application monitoring.
- Experience leading architecture POCs and technology evaluations.

Key Competencies

- Solution Architecture
- Enterprise Architecture
- Java & Spring Boot
- Python
- GenAI / Agentic AI
- LLMs
- RAG
- Prompt Engineering
- Vector Databases
- LangChain / LangGraph / CrewAI / AutoGen / Semantic Kernel
- Cloud Architecture – AWS / Azure / GCP
- Microservices
- REST APIs
- Docker & Kubernetes
- CI/CD
- AI Security & Governance
- Responsible AI
- Technical Leadership
- Stakeholder Management

Education

Bachelor's or Master's degree in Computer Science, Information Technology, Engineering, or a related discipline.

📌 Solution Architect_GenAI (Agentic AI) (Hyderabad)
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