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Senior AI Engineer
Aspire Software. Experiment with agentic and multi-agent development workflows on real work .
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in designing, building, and deploying AI-powered features, with a strong focus on LLM applications, prompt engineering, and cloud-native architecture. Proficient in modern web application development and integrating AI systems while ensuring quality and performance.
Highest-signal resume keywords
AI/LLM-Powered Feature DevelopmentPrompt EngineeringCloud-Native ArchitectureJava Spring and Oracle DatabaseAutomated Testing Frameworks
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
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Hard Skills
AI Model EvaluationRetrieval-Augmented Generation (RAG)TypeScript/Node.jsPythonGoReactAngularREST APIsTest Driven Development (TDD)CI/CD Pipelines
Tools & Technologies
OpenAIAWS BedrockAWS SageMakerSpring AILangChain/LangGraphLlamaIndexJestReact Testing LibraryWebpackBabel
Industry Keywords
AI WorkflowAgentic DevelopmentData PrivacyResponsible AI PracticesModern JavaScript FeaturesMobile App DevelopmentUI/UX Design for AI Features
Tech Stack
Tools & technologiesAndroidAngularAWSBabelCloudiOSJavaJavaScriptJestKotlinNode.jsOraclePythonReactReact NativeSCSSSpringSQLSwiftTypeScriptWebpackYarnGo
About the role
Key responsibilities & impact- Experiment with agentic and multi-agent development workflows on real work
- Share AI workflow learnings through demonstrations, best practices, documentation, and teammate support
- Apply AI across coding, testing, code review, CI/CD, legacy code, and platform migration
- Design, build, and ship AI-powered product features such as LLM assistants, chatbots, summarization, translation, classification, predictive analytics, personalization, anomaly detection, and intelligent automation
- Build LLM applications and agents using prompt engineering, RAG, tool/function calling, structured outputs, and multi-step agentic workflows
- Evaluate, select, and integrate AI models, APIs, and frameworks while balancing quality, latency, and cost
- Establish AI evaluation and quality practices, including test datasets, automated evaluations, prompt/model regression testing, and production monitoring
- Implement guardrails, PII handling, prompt-injection mitigation, and fallback behavior for safe and reliable AI features
- Partner with product teams to identify and prototype customer-facing AI use cases
- Stay current with AI models, tools, and techniques and apply practical improvements
- Contribute to a ground-up v2 platform rebuild on a modern AI-first stack
- Maintain and enhance the existing JSP, Java Spring, Oracle Database, and PL/SQL platform during migration
- Design and implement robust, scalable, and secure web applications
- Collaborate with cross-functional teams on new features
- Ensure application performance, quality, and responsiveness
- Identify and resolve bottlenecks and bugs
- Maintain code quality, organization, and automation
- Participate in code reviews
- Implement and manage CI/CD pipelines, including for AI-powered services
Requirements
What you’ll need- Proven experience designing, building, and deploying AI/LLM-powered features to production, including chatbots, assistants, summarization, recommendation engines, predictive analytics, and personalization
- Hands-on experience with LLM APIs and platforms such as OpenAI, Anthropic, AWS Bedrock, and AWS SageMaker
- Experience with prompt engineering, tool/function calling, and structured outputs
- Experience building retrieval-augmented generation (RAG) pipelines, including embeddings, chunking, and vector search
- Familiarity with AI orchestration and agent frameworks such as Spring AI, LangChain/LangGraph, and LlamaIndex
- Familiarity with the Model Context Protocol (MCP)
- Experience evaluating and monitoring AI systems, including evaluation datasets, output quality, latency, cost, and production failure modes
- Understanding of AI risks and mitigations, including hallucinations, prompt injection, data privacy, and responsible AI practices
- Hands-on experience with agentic development using coding agents such as Claude Code, Cursor, and GitHub Copilot
- Strong experience with modern languages and stacks such as TypeScript/Node.js, Python, and Go
- Experience with cloud-native architecture and modern databases
- Experience developing modern web applications using React or Angular
- Ability to work in and understand Java, Spring, JSP, Oracle Database, and PL/SQL; hands-on experience is a plus
- Experience integrating front-end applications with back-end services using REST APIs and third-party APIs
- Experience with automated testing frameworks for React, including Jest and React Testing Library
- Understanding of modern JavaScript features, asynchronous programming, and CSS preprocessors such as SASS
- Familiarity with Test Driven Development (TDD)
- Familiarity with AWS and cloud-native services
- Familiarity with Webpack, Babel, ESLint, npm, and yarn
- Familiarity with Material-UI and Tailwind
- Bonus: Proficiency in Python for AI/ML work
- Bonus: Grounding in ML fundamentals or experience fine-tuning models
- Bonus: Experience leading or contributing to a major platform rebuild or legacy-to-modern migration
- Bonus: Experience in mobile app development such as React Native, Swift/iOS, or Kotlin/Android
- Bonus: Familiarity with UI/UX design for AI features