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Salary
≈ $13k – $31k per year (Estimated)
Location
Hybrid (Bengaluru, India)
Seniority
Staff · 8+ years exp
Employment
Full-Time

Confirmed on the employer's own hiring board on Oct 24, 2026. First seen by Alion on Oct 21, 2026. Cognizant scores A on the Alion truth index.

Overview
Company
Impact
Profile match
Cognizant is an American information technology services and consulting company founded in 1994 as an in-house technology unit of Dun and Bradstreet in Chennai, India, and headquartered in Teaneck, New Jersey. It builds, integrates and operates software and infrastructure for large enterprises, with particularly deep positions in healthcare, financial services, insurance and life sciences, delivered by a global workforce of more than three hundred thousand people concentrated in India. Listed on Nasdaq, the company competes with the large Indian and global systems integrators and has reoriented its offerings around cloud migration, data platforms and AI-assisted engineering.

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

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