Java Full stack GenAI (5Yrs - 10Yrs)

Mphasis; Pune District, Chennai; On-site; INR 1,200,000 - 1,800,000; Full time

Job summary

Mphasis invites a Java Full Stack professional with AI/ML expertise to design and implement enterprise-grade solutions for banking and financial services. You will work across front-end, back-end, and AI agentic components, and collaborate with customers to translate goals into scalable software.

The role involves building AI agents, deploying in cloud environments, ensuring security and compliance, and driving code quality with CI/CD, Playwright/Selenium tests, and Spec-driven development.

Qualifications

• Experience in Python and reviewing AI-generated code for enterprise use.
• Experience with AI-assisted development tools (GitHub Copilot, Claude, Cursor).
• Proficiency with LangChain/LangGraph and cloud platforms (GCP/Azure).
• Experience with API design, microservices, and modern architectures.
• Ability to read code in client stacks (Java/Spring, .NET, Node.js, Python), REST APIs and data models.
• Familiarity with static analysis and code parsing tools.
• Experience with CI/CD, DevSecOps and automated testing.
• Experience with test automation tools like Playwright or Selenium.

Responsibilities

• Collaborate with customers and stakeholders to understand business goals, strategy, pain points, opportunities.
• Map processes and workflows, define success metrics and KPIs.
• Assess current state & technology landscape, prioritize use cases and ROI.
• Design technology solutions, AI workflows, and integrations with data security considerations.
• Build AI agents, copilots, APIs, services, and RAG orchestration.
• Review AI-generated artifacts and ensure quality and alignment to specs.
• Apply prompt/context engineering to improve solution outcomes.
• Implement or enhance the SDD framework for application functionalities.
• Develop code analysis capabilities using the SDD framework.

Skills

Python FPS??

AI/LLM frameworks LangChain LangGraph

GCP/Azure

Spec-Driven Development

APIs & Microservices

REST APIs & Data Models

Static analysis / code parsing

CI/CD & DevSecOps

Playwright / Selenium

Tools

GitHub Copilot

LangChain

CodeQL

Tree-sitter

Sourcegraph

Job description

Work Mode- 5Days Work from office

Java Full stack + AI/ML Algorithms + AI Agentic Solutions + Building Agentic + Deployment / Implementation + Banking and Financial Experience

Key Responsibilities

• 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 (GitHub SpecKit) 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 productionize CI/CD, automation, security, access, compliance, monitoring, logging, observability, performance tuning, scalability
• Review and ensure compliance with enterprise security, governance, DevSecOps, 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

Required Technical Skills

• 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 GitHub Copilot, Claude, Cursor, or equivalent platforms.
• Expert AI/LLM framework LangChain/LangGraph, GCP/Azure, GraphDB/Vector Database
• Experience working with Spec-Driven Development methodologies (GitHub Spec Kit or comparable approaches).
• Hands-on experience with APIs, microservices, and modern application architectures.
• Ability to read and reason about code in the clients 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 parsing, call graphs, dependency analysis, or tools such as Tree-sitter, CodeQL, or Sourcegraph)
• Familiarity with CI/CD, DevSecOps, automated testing, and deployment pipelines.
• Experience with test automation frameworks such as Playwright, Selenium, or equivalent.

Professional Skills

• Strong problem-solving and analytical capabilities.
• Customer-facing communication and consulting skills.
• Ability to work independently in fast-paced environments.
• Experience collaborating with cross-functional and distributed teams.
• Strong ownership mindset with a focus on measurable business outcomes.

Preferred Qualifications

• Experience in Banking & Financial Services (BFS) domain.
• Exposure to Agentic SDLC, Spec-Driven Development, or AI-assisted delivery models.
• Understanding of cloud-native architectures and platform engineering.