Solution Architect / Pre-Sales

Key Responsibilities:

• Lead end-to-end solution design and pre-sales activities across enterprise applications and AI-driven software initiatives.
• Architect scalable, secure, and cloud-native solutions integrating microservices, APIs, and generative AI components.
• Drive & own proposal development, estimation, RFP responses, and client presentations.
• Establish and implement DevSecOps practices, CI/CD frameworks, and test automation strategies to ensure quality, security, and agility.
• Define MLOps/LLMOps pipelines for model development, deployment, monitoring, and continuous improvement.
• Enforce AI guardrails covering model governance, data privacy, ethical use, prompt management, and Responsible AI compliance.
• Promote spec-driven development strategies using automation, reusable assets, and reference architectures.
• Partner with clients in architecture workshops, PoCs, and technical assessments to craft tailored transformation strategies.
• Mentor engineering teams and contribute to go-to-market assets, accelerators, and solution blueprints.

Qualifications:

• 10–15 years of experience in solution architecture, pre-sales, and enterprise application development.
• Strong expertise in one of the cloud-native stacks (Azure, AWS, GCP), DevSecOps toolchains (Azure DevOps, GitHub, Terraform, Kubernetes), and API/microservices architecture.
• Hands-on knowledge of AI and LLM-based application design, prompt engineering, and vector databases.
• Experience with MLOps/LLMOps frameworks (Azure ML, AWS Bedrock/SageMaker, GCP Vertex AI).
• Proficiency in modern programming and testing frameworks (Python, Java, .NET, Selenium, Cypress, JUnit, NUnit).
• Deep understanding of Responsible AI principles, security-by-design, and compliance in enterprise environments.
• Excellent storytelling, proposal creation, and client engagement skills.