#SoftwareEngineerII #AIEngineer #GenAIEngineer #JavaDeveloper #FullStackDeveloper

Software Engineer II — Full Stack Java & AI/GenAI Engineer

5+ years building production-grade Java backends, GenAI applications, and MuleSoft integrations at Mutual of Omaha. Spring Boot · Amazon Bedrock · RAG · Multi-Agent · Event-Driven Architecture.

LLM Applications · RAG · Multi-Agent Systems · Frontend Engineering

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Chicago Area · Open to relocation within US

AI Engineer
5+
Years Full Stack & AI Engineering
3
Companies · Enterprise & Banking
SWE II
Mutual of Omaha · AI Focus

Who I am as an engineer

I design and ship production-grade GenAI systems, MuleSoft integrations, and microservices at Mutual of Omaha, where I'm a Software Engineer II focused on AI.

I'm a Software Engineer II with 5+ years building production-grade backend systems, GenAI applications, and modern frontends across insurance and banking. At Mutual of Omaha I design ML and generative AI solutions for a Workplace Solutions division — owning everything from proof of concept through production rollout. I've built event-driven microservices on Kafka and AWS, shipped LLM-powered internal tools with Amazon Bedrock and OpenAI, and architected MuleSoft integrations for producer onboarding systems serving 50K+ policyholders.

I care about clean abstractions, observable systems, and responsible AI practices. I mentor engineers on LLM adoption, context engineering, and orchestration patterns, and I collaborate with architects and business stakeholders to shape AI strategy and roadmap.

What I'm looking for

AI Engineer, GenAI Engineer, and Senior Full Stack roles — designing LLM-powered products, driving API/integration strategy (including MuleSoft and event-driven architectures), and building production-grade systems on AWS.

Currently deepening: Agentic AI workflows, MLOps practices, AI Governance frameworks, and real-time data pipelines.

Primary Stack

  • Designing and shipping ML and GenAI solutions for Mutual of Omaha’s Workplace Solutions division
  • Architected MuleSoft integrations for enterprise producer onboarding and management systems
  • Built LLM-powered internal tools using Amazon Bedrock, OpenAI API, and custom prompt engineering
  • Architected event-driven microservices with Kafka and AWS (Lambda, SQS, EC2, S3)
  • Delivered full-stack features across Angular, Next.js, Vue.js, Spring Boot, and PostgreSQL

Strengths

  • Translating business requirements into AI strategy, technical roadmaps, and measurable outcomes
  • Building and governing AI systems responsibly — prompt engineering, model evaluation, A/B testing, and AIOps
  • Mentoring engineers on LLM adoption, context engineering, and orchestration patterns
  • Balancing technical excellence with delivery — CI/CD, observability, and operational resilience
  • Communicating architectural trade-offs clearly across engineering, product, and business stakeholders

Based in

  • Chicago, IL · Open to relocation within the US · Active in Agile/Scrum, PR reviews, and cross-functional team collaboration
  • Mentoring engineers on LLM adoption — building reusable templates and reference implementations

Technologies I work with

A focused stack around Java, Spring Boot, microservices, AWS, and GenAI — grouped by proficiency.

95%

Expert

5+ years · Production at Mutual of Omaha & MUFG

Java 11/17Spring BootSpring Data JPAHibernateREST APIsMicroservicesGroovyGrails
78%

Proficient

Shipped in production across 3 companies

AWS (EC2 · S3 · Lambda · SQS · Bedrock · CDK)MuleSoftKafkaAngularReactNext.jsVue.jsSvelte/SvelteKitTypeScriptNode.jsHTML/CSSTailwindCSSGraphQLPostgreSQLMySQLDockerJenkinsGitHub ActionsJUnitMockito
60%

Applied AI & MLOps

Applied AI & MLOps

Amazon BedrockOpenAI APIRAG PipelinesFAISSMulti-Agent / Agentic ArchitecturePythonFastAPIPrompt & Context EngineeringLLM IntegrationMachine LearningModel EvaluationA/B TestingAIOpsMLOpsAI GovernanceEthical AISageMakerAWS CDKTerraformKubernetesGitHub Copilot
EP

Engineering Practices

Applied daily across enterprise delivery

Object-Oriented DesignDesign PatternsEnterprise Application ArchitectureAutomated Testing (E2E, Integration, Regression)ObservabilityProduction SupportLegacy System ModernizationRoot-Cause AnalysisAI Governance FrameworksEthical AI / Responsible AIRegulatory ComplianceSecure Model DeploymentAgile/ScrumCode ReviewsCI/CD

Things I have built

Real applications with working APIs, clean architecture, and production-ready code.

GenAIRAGPython

AskDocs AI

RAG-powered PDF chatbot that lets users upload any document and ask grounded questions. Solves the problem of long manuals and research papers where users can't quickly find specific answers.

What I built

  • PDF ingestion pipeline into FAISS vector store
  • Semantic search returning top-k passages with page citations
  • Amazon Bedrock (Claude) prompt chain for multi-turn Q&A
  • FastAPI backend with Streamlit chat UI

What I gained

  • End-to-end RAG architecture
  • Production prompt engineering on Bedrock
  • Vector database design patterns
PythonFastAPIStreamlitAmazon BedrockFAISS
View on GitHub
GenAICustomer SupportPython

SupportGPT

AI customer support chatbot that auto-handles FAQs and escalates frustrated customers. Solves the cost and latency problem of routing every ticket through a human agent.

What I built

  • FAQ knowledge layer with 80%+ auto-resolution rate
  • Real-time sentiment analysis to detect frustration
  • Auto-escalation flow with full context handoff
  • FastAPI service with chat history persistence

What I gained

  • Conversational AI design
  • LLM-driven workflow routing
  • Sentiment analysis integration
PythonFastAPIAmazon BedrockSentiment Analysis
View on GitHub
GenAINL-to-SQLPython

SQLGenie

Natural-language to SQL translator with a safety layer. Lets business users ask questions in plain English without risking destructive database operations.

What I built

  • NL → SQL prompt pipeline tuned for Bedrock Claude
  • Static analyzer blocking INSERT/UPDATE/DELETE/DROP
  • Schema-aware context injection for accurate SQL
  • FastAPI endpoint with structured error responses

What I gained

  • LLM guardrails & safety design
  • Structured prompt engineering
  • SQL query validation patterns
PythonFastAPIAmazon BedrockNL-to-SQL
View on GitHub
GenAIMulti-AgentPython

AgentFlow

Multi-agent orchestration system where Planner, Researcher, and Summarizer agents collaborate to answer complex queries — without LangChain.

What I built

  • Custom agent base class on top of Bedrock
  • Planner agent decomposing goals into sub-tasks
  • Researcher agent with tool use for fact gathering
  • Summarizer agent synthesizing final structured answers

What I gained

  • Multi-agent architecture patterns
  • Bedrock agent orchestration
  • Custom LLM workflow design
PythonFastAPIAmazon BedrockMulti-Agent
View on GitHub
JavaSpring BootAWS

AI Document Intelligence Platform

End-to-end document processing pipeline: ingest → OCR → AI extraction → dashboard. Solves manual data entry for invoices and scanned documents at scale.

What I built

  • Spring Boot ingestion service publishing to AWS SQS
  • AWS Textract integration for OCR and form extraction
  • Structured data extraction with validation rules
  • React dashboard for reviewers with audit trails

What I gained

  • Event-driven Spring + AWS messaging
  • OCR + AI extraction pipelines
  • Full-stack delivery on AWS
JavaSpring BootAWS TextractS3SQSReact
View on GitHub
JavaKafkaMicroservices

Banking Transaction Microservices

Banking platform split into auth, transactions, and notifications microservices coordinated via Kafka. Solves tight coupling of a monolithic banking backend.

What I built

  • Auth service with JWT issuance and refresh flow
  • Transactions service publishing domain events to Kafka
  • Notifications service consuming events for email/SMS
  • Dockerized services with Kubernetes manifests

What I gained

  • Event-driven microservices patterns
  • Container orchestration with K8s
  • Banking domain modeling
JavaSpring BootKafkaDockerKubernetes
View on GitHub
JavaAngularFull Stack

Insurance Customer Portal

Full-stack policy, claims, and account management portal for insurance customers. Centralizes self-service workflows with JWT auth and a clean Angular component architecture.

What I built

  • Spring Boot REST APIs for policies, claims, and accounts
  • Angular reactive forms with field-level validation
  • JWT authentication with role-based access control
  • PostgreSQL schema with optimized indexes

What I gained

  • Full-stack delivery ownership
  • Auth & RBAC patterns
  • Angular component architecture
JavaSpring BootAngularPostgreSQLJWT
View on GitHub

Licenses & Certifications

Verified credentials from industry platforms.

CodeSignal

Building GenAI Applications with AWS

Completed the full learning path. Skills in AI/ML fundamentals, autonomous workflow automation, and RAG systems with vector databases.

Issued Jun 2026Learning PathGenAI · AWS
View certificate →
CodeSignal

Putting Bedrock Models to Action with Strands Agents

Building agentic workflows on top of Amazon Bedrock models with Strands.

Issued Jun 2026Bedrock · Agents
View certificate →
CodeSignal

Basics of GenAI Foundation Models with Amazon Bedrock

Foundations of GenAI on AWS — prompt design, model selection, and invoking foundation models through Amazon Bedrock.

Issued Jun 2026Foundation Models · Bedrock
View certificate →
CodeSignal

Managing Data for GenAI with Bedrock Knowledge Bases

Creating and configuring Bedrock Knowledge Bases, document ingestion, vector storage with S3, and building retrieval systems.

Issued Jun 2026RAG · Knowledge Bases · S3
View certificate →
HackerRank

Software Engineer Certificate

Verified Software Engineer certification covering problem solving, REST APIs, and full-stack engineering fundamentals.

Issued May 2026Software Engineering
View certificate →

Let's talk.

I'm actively targeting AI Engineer, GenAI Engineer, and Senior Full Stack roles — especially teams building LLM-powered products, MuleSoft integrations, event-driven microservices, or cloud-native systems on AWS.

Reach out directly

Based in Chicago area · Open to hybrid/remote roles across the US

✉️ rajeshdevandla11@gmail.com LinkedIn GitHub

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