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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.
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