#SoftwareEngineerII #AIEngineer #GenAIEngineer #JavaDeveloper #FullStackDeveloper

AI 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 Software & 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 roles — designing LLM-powered products, driving API and integration strategy, 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 IntegrationModel EvaluationA/B TestingAIOpsAI 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 engineering 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 roles — especially teams building LLM-powered products, agentic systems, event-driven services, 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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