Architect Advanced

Mphasis is seeking a highly motivated Forward Deployed Engineer (FDE) to bridge business challenges and technology solutions through AI-assisted engineering, automation, and modern software delivery practices.

As an FDE, you will work directly with customers to translate business requirements into scalable technology solutions. You will leverage AI-native engineering approaches, Agentic SDLC practices, and automation frameworks to accelerate solution delivery while ensuring enterprise-grade quality and governance. The ideal candidate will design and deploy solutions using AIDLC (spec-driven development).

• Work closely with customers and stakeholders to understand business goals, strategy, pain points, opportunities
• Map processes and workflow, define success metrics and KPIs
• Assess current state & technology landscape, priorities use cases, estimate ROI,
• Design technology solutions, AI/Agent workflows, integrations, data requirements, security and risk requirements
• Build AI agents, copilots, applications, APIs, services, integration with enterprise systems, RAG, orchestration
• Design, generate and validate AI-generated code and engineering artifacts, and drive deployment of enterprise-grade applications, integrations, and AI-powered solutions
• Review and validate AI-generated artifacts including requirements, design documents, code, and technical specifications.
• Apply prompt engineering, context engineering, and AI enablement techniques to improve solution outcomes.
• Customize SDD framework (Git Hub Spec Kit) to implement or enhance the application functionalities.
• Build the code analysis capability that scans the application code base (UI components, routes, controllers/services, API definitions, data models, validation and business-rule logic) using SDD Framework.
• Extract user flows, functional rules, boundary conditions, error paths, and integration points from the code using SDD framework
• Convert the extracted understanding into structured, reviewable specs using the Spec Kit workflow (constitution, specify, plan, tasks, implement).
• Handle large or legacy code bases through chunking, indexing, dependency mapping, and context management so results stay accurate.
• Review and validate AI-generated test designs, test cases, Playwright automation scripts, and quality engineering assets to ensure functional accuracy, adequate coverage, maintainability, and production readiness.
• Deploy and product ionize CI/CD, automation, security, access, compliance, monitoring, logging, observability, performance tuning, scalability
• Review and ensure compliance with enterprise security, governance, Dev Sec Ops , and quality standards.
• Develop user onboarding, training, go-live support
• Drive user adoption, measure business impact, optimize user experience, communicate outcomes
• Identify new user cases, expansion opportunities, refine model, prompts, agents
• Improve and refine processes, automation

• Strong software engineering background with 5–7 years of experience.
• Strong proficiency in Python, with the ability to review, validate, debug, and optimize AI-generated code for enterprise use.
• Experience leveraging AI-assisted development tools such as Git Hub Copilot, Claude, Cursor, or equivalent platforms.
• Expert AI/LLM framework Lang Chain/Lang Graph, GCP/Azure, GraphDB/Vector Database
• Experience working with Spec-Driven Development methodologies (Git Hub Spec Kit or comparable approaches).
• Hands-on experience with APIs, microservices, and modern application architectures.
• Ability to read and reason about code in the client’s stack (for example Java/Spring, .NET, Node.js, C++ or Python), including REST APIs and data models.
• Experience with static analysis or code parsing techniques (AST…