Lead Solution Architect GenAI & Cloud

Experience: 9-11 Years

Location: Gurgaon (Hybrid)

Budget: Up to 35 LPA

Employment Type: Full-Time

Our Client is looking for a hands-on Lead Solution Architect to lead the design and development of innovative technology solutions across Generative AI, cloud, and emerging technologies. The role involves taking PoCs, prototypes, and MVPs to enterprise-grade production while ensuring scalability, security, and performance.

Key Responsibilities

Lead solution architecture for PoCs, prototypes, and MVPs, ensuring production readiness.

Provide hands-on technical guidance across applications, cloud, integrations, data, and AI.

Design secure, scalable, resilient, and cost-effective cloud-native solutions.

Architect AI/ML, Generative AI, RAG, and Agentic AI solutions.

Guide the implementation of APIs, microservices, containers, serverless technologies, CI/CD, and DevSecOps.

Establish reusable architecture patterns, engineering standards, and reference architectures.

Collaborate with security, cloud, enterprise architecture, and delivery teams.

Evaluate emerging technologies and platforms for enterprise adoption.

Mentor developers through design reviews, code reviews, and technical coaching.

Ensure successful transition of validated solutions to enterprise production teams.

Mandatory Skills

9-11 years of technology experience with strong solution, application, or cloud architecture expertise.

Hands-on software development and experience taking PoCs/MVPs into production.

Strong cloud knowledge, preferably AWS and/or Azure.

APIs, microservices, distributed systems, Docker, and Kubernetes.

CI/CD, DevSecOps, Infrastructure as Code (IaC), application security, and observability.

Practical knowledge of AI/ML and Generative AI architecture.

Strong technical leadership, problem-solving, and stakeholder communication skills.

Technical Skills

Cloud & Infrastructure: AWS, Azure, Kubernetes, Docker, Serverless.

AI & Emerging Technologies: Generative AI, LLMs, RAG, Agentic AI, MCP, Vector Databases, AI Guardrails.

Development: Python, Java, JavaScript/TypeScript, React/Next.js, APIs.

Engineering & DevSecOps: CI/CD, GitHub, IaC, automated testing, security scanning.

Good-to-Have Skills

Hands-on experience with LLMs, RAG pipelines, AI agents, vector databases, and AI guardrails.

Enterprise security, privacy, risk management, and architecture governance.

Experience establishing reusable engineering practices and mentoring technical teams.