Senior AI Engineer - HYPR
Valsoft · Beirut
Aspire Software is looking for a Senior AI Engineer to join our team in Lebanon.
Here is a little window into our company: Aspire Software operates and manages wholly owned software companies, providing mission-critical solutions across multiple verticals. By implementing industry best practices, Aspire delivers a time sensitive integration process, and the operation of a decentralized model has allowed it to become a hub for creating rapid growth by reinvesting in its portfolio.
About the Job:
We're looking for an AI-first Senior Engineer to help move our team from light AI use to agent-driven, multi-agent development. You'll build AI-powered product features end to end, work agent-first in your own day-to-day development, and share what works so the rest of the team can follow. You're also a strong full-stack engineer with modern stack experience, ready to play a key role in an upcoming ground-up rebuild (v2) of our platform while keeping our existing Java/Oracle platform running in the meantime.
AI-first development:
- Be a hands-on early adopter: try agentic and multi-agent development workflows on real work, and find what works for our codebase and team.
- Share what you learn by demonstrating workflows, contributing best practices and documentation, and helping teammates get up to speed.
- Apply AI across the development lifecycle, from coding and testing to code review, CI/CD, and work on our legacy codebase and platform migration.
AI product engineering:
- Design, build, and ship AI-powered product features end to end, such as LLM-based assistants and chatbots, summarization, translation, classification, predictive analytics, personalization, anomaly detection, and intelligent automation.
- Build LLM applications and agents using prompt engineering, retrieval-augmented generation (RAG), tool/function calling, structured outputs, and multi-step agentic workflows.
- Evaluate, select, and integrate AI models, APIs, and frameworks into our applications and internal tooling, balancing quality, latency, and cost for each use case.
- Set up evaluation and quality practices for AI features: test datasets, automated evals, regression testing of prompts and models, and production monitoring for accuracy, latency, and cost.
- Make AI features safe and reliable with guardrails, data privacy and PII handling, prompt-injection mitigation, and sensible fallback behavior.
- Partner with product teams to identify customer-facing use cases where AI can drive measurable value and competitive advantage, and rapidly prototype to validate them.
- Stay current with the fast-moving AI landscape (models, tools, and techniques) and bring practical improvements into the product and the team.
Full-stack engineering:
- Play a key role in a ground-up rebuild (v2) of our platform on a modern stack, designed from the start for AI-first development.
- Maintain and enhance our existing platform (JSP, Java Spring, Oracle Database, PL/SQL) through the transition and help plan and execute the migration to v2.
- Design and implement robust, scalable, and secure web applications.
- Collaborate with cross-functional teams to define, design, and implement new features.
- Ensure the performance, quality, and responsiveness of applications.
- Identify and resolve bottlenecks and bugs.
- Help maintain code quality, organization, and automation.
- Participate in code reviews.
- Implement and manage continuous integration and continuous delivery (CI/CD) pipelines, including for AI-powered services.
Requirements
AI engineering:
- Proven experience designing, building, and deploying AI/LLM-powered features to production (e.g., chatbots and assistants, summarization, recommendation engines, predictive analytics, personalization).
- Hands-on experience with LLM APIs and platforms (e.g., OpenAI, Anthropic, AWS Bedrock, AWS SageMaker), including prompt engineering, tool/function calling, and structured outputs.
- Experience building retrieval-augmented generation (RAG) pipelines, including embeddings, chunking, and vector search (e.g., pgvector, OpenSearch, Oracle AI Vector Search).
- Familiarity with AI orchestration and agent frameworks (e.g., Spring AI, LangChain/LangGraph, LlamaIndex) and protocols such as the Model Context Protocol (MCP).
- Experience evaluating and monitoring AI systems: building eval datasets, measuring output quality, and tracking latency, cost, and failure modes in production.
- Understanding of AI risks and mitigations, including hallucinations, prompt injection, data privacy, and responsible AI practices.
- Hands-on experience with agentic development, such as running coding agents (e.g., Claude Code, Cursor, GitHub Copilot) on multi-step tasks, coordinating multiple agents, and configuring agent rules, context, and MCP integrations.
- Curiosity and willingness to experiment with new AI workflows, and to share results openly with the team, including what didn't work.
Software engineering:
- Strong experience with modern languages and stacks (e.g., TypeScript/Node.js, Python, Go), cloud-native architecture, and modern databases, including designing new systems from the ground up.
- Experience developing modern web applications using React (functional components, hooks, state management like Redux) or Angular.
- Ability to work in and understand our existing platform (Java, Spring, JSP, Oracle Database, PL/SQL); hands-on experience with these is a plus.
- Experience integrating front-end applications with back-end services using REST APIs, and with third-party APIs (e.g., Google Maps JavaScript API).
- Experience with automated testing frameworks for React (Jest, React Testing Library) and mocking API responses in tests.
- Understanding of modern JavaScript features (ES6+), asynchronous programming (promises, async/await), and CSS preprocessors like SASS.
- Familiarity with Test Driven Development (TDD).
- Familiarity with AWS and cloud-native services.
- Familiarity with tools like Webpack, Babel, ESLint, and package managers (npm, yarn).
- Familiarity with modern UI frameworks like Material-UI and Tailwind.
Nice to have:
- (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 (e.g., React Native, Swift/iOS, Kotlin/Android).
- (Bonus) Familiarity with UI/UX design, including designing intuitive user experiences for AI features.