AI-Augmented Software Engineer

Job Summary: AI augmented software engineer role focused on building secure and scalable customer service platforms for mortgage products using Angular microservices ASP Net Core or Core Java while orchestrating MCP enabled GenAI solutions and advanced RAG frameworks to improve agent productivity self-service experiences and knowledge workflows in a hybrid work model for a global financial enterprise

Experience: 8 - 12 years

Required Skills: Technical Skills: Angular 13-18 MCP (Model Context Protocol) GENAI/LLM Fundamentals GenAI Basics Knowledge Engineering for AI RAG Consumption Advanced RAG Frameworks DB - SQL & No SQL Microservices ASP.Net Core Java Domain Skills: Customer service (Mortgage)

Responsibilities : -

       Design and implement responsive front end applications using Angular versions thirteen to eighteen that deliver intuitive customer service experiences for mortgage journeys while meeting accessibility and performance expectations

       Develop and maintain secure microservices using ASP Net Core or Core Java that support high volume mortgage customer interactions with emphasis on resilience observability and operational stability

       Integrate Model Context Protocol based services with existing application components to orchestrate context rich interactions between core systems and GenAI powered assistance flows

       Build and refine retrieval augmented generation pipelines that combine structured SQL data and unstructured No SQL content to produce accurate and auditable responses for customer service scenarios

       Engineer production ready GenAI and LLM solutions that encapsulate prompt patterns safety constraints and monitoring hooks to enhance customer interactions without compromising compliance

       Design knowledge engineering workflows that curate validate and version domain assets for AI RAG consumption ensuring that mortgage customer service content remains current consistent and discoverable

       Create scalable data access layers using SQL and No SQL stores that support flexible query patterns for mortgage customer profiles loan servicing events and contact center histories

       Collaborate with product owners business analysts and operations teams in the mortgage customer service domain to translate service journeys pain points and compliance rules into technical solutions

       Implement observability practices including logging metrics and tracing across microservices and AI components to enable proactive issue detection and continuous service quality improvement

       Apply secure coding practices and defensive design to protect sensitive mortgage and customer data while aligning with enterprise standards for authentication authorization and data retention

       Conduct code reviews technical walkthroughs and knowledge sharing sessions to promote consistent engineering practices for AI augmented applications across the team

       Optimize application performance by profiling hotspots tuning database queries refining caching strategies and improving model interaction patterns to reduce latency and operational cost

       Partner with testing and operations teams to define automated test coverage deployment pipelines and rollback strategies that keep AI components and microservices reliable in hybrid environments

       Qualifications -Offer eight to twelve years of hands on software engineering experience delivering enterprise applications using Angular microservices and modern backend frameworks in financial or similar regulated domains

       Demonstrate strong proficiency with Angular versions thirteen to eighteen including modular architecture state management testing strategies and integration with RESTful and event driven backends

       Exhibit proven experience with GenAI and LLM fundamentals including prompt design grounding techniques and evaluation strategies tailored to customer service workflows Show practical experience in building or supporting advanced RAG frameworks that blend SQL and No SQL sources with vector retrieval methods to improve answer relevance and traceability

       Display solid understanding of Model Context Protocol concepts and implementation patterns for orchestrating context across multiple AI agents tools and enterprise services

       Possess strong skills in ASP Net Core and Core Java for implementing secure scalable and maintainable microservices with clean separation of concerns and reusable components

       Bring hands on experience with relational SQL and document or key value No SQL databases including schema design query optimization and data modeling for customer centric workloads

       Provide domain experience in customer service for mortgage including servicing processes inquiry handling and regulatory considerations with additional mortgage loan exposure considered an advantage

       Communicate clearly with cross functional stakeholders and contribute to documentation runbooks and knowledge artifacts that support sustainable operations in a hybrid work model

       Adapt to evolving AI and GenAI technology landscapes by continuously learning experimenting and applying new techniques that improve customer outcomes and operational efficiency.

Certifications Required: Preferred certifications include Professional Machine Learning Engineer or equivalent AI and cloud credentials