Senior AI & Software Engineer

Role Overview We are seeking a talented and versatile Senior AI & Software Engineer to join our technology team onsite at our headquarters. In this role, you will bridge the gap between traditional enterprise software engineering and modern applied AI. You will be responsible for designing resilient backend architectures, deploying scalable cloud infrastructure, and building production-ready generative AI solutions—including intelligent agents, advanced RAG systems, and conversational workflows.

Key Responsibilities

• AI & Agentic Systems: Architect and implement intelligent generative AI applications, utilizing tool routing, agentic workflows, and advanced retrieval-augmented generation (RAG) pipelines.
• Backend Architecture: Design, build, and maintain high-performance, scalable microservices and RESTful APIs capable of handling high-throughput production traffic.
• Voice & Conversational AI: Develop and optimize low-latency conversational interfaces, real-time voice agents, and custom speech-to-text (STT) or text-to-speech (TTS) models.
• Cloud & DevOps: Own the end-to-end cloud infrastructure, leveraging containerization, Infrastructure as Code (IaC), and automated CI/CD pipelines to ensure secure and seamless deployments.
• Data Engineering: Build robust data pipelines and integrate both traditional databases and vector databases to support fast, accurate semantic search and analytics.

Key Requirements

• Experience:
  • 5+ years of professional experience in backend or full-stack software development.
  • 3+ years of hands-on experience building and deploying generative AI solutions and LLM-powered applications in production environments.
• Technical Skills:
  • Strong programming skills in Python, JavaScript, and TypeScript.
  • Deep expertise in backend frameworks such as Node.js (NestJS/Express) and FastAPI.
  • Proven experience with AI orchestration frameworks like LangChain or LlamaIndex.
  • Proficient with relational, document, and vector databases (e.g., PostgreSQL, MongoDB, Qdrant).
  • Solid hands-on experience with cloud platforms (AWS preferred), containerization (Docker), and infrastructure orchestration (Terraform/CloudFormation).
• Education & Professional Standing:
  • Bachelor's degree in Computer Science, Software Engineering, IT, or a related technical field.
  • Professional engineering licensing or relevant cloud/AI certifications are highly valued.