About InterOpera
InterOpera is pioneering intelligence infrastructure to eliminate key enterprise pain points, driving cost efficiency, profitability, and scalable growth. Through our real-time decision-making capabilities, we empower clients to identify challenges, generate actionable insights, implement solutions, and track outcomes to ensure sustained success. Our solutions span sales optimization, risk management, and energy efficiency, helping businesses harness data-driven strategies and seamless automation to enhance operational resilience and long-term value creation.
We're looking for a Senior Software Engineer, AI-Native Enterprise Platform who is passionate about building production-grade AI systems, thrives in a fast-paced startup environment, and wants to shape the future of enterprise decision-making through agentic AI, RAG, and modern software engineering. We’d love to hear from you.
Responsibilities
AI-Native Product Engineering
Architect and ship production-grade multi-step AI agents with planning, memory, and tool usage capabilities to automate enterprise workflows
Design, build, and operate Retrieval-Augmented Generation (RAG) pipelines over proprietary enterprise datasets
Evaluate, deploy, and optimize small/specialized LLMs (sLLMs), including self-hosted deployments for cost efficiency, latency optimization, and data residency requirements
Develop evaluation frameworks to measure AI performance, including faithfulness, hallucination rates, latency, and instruction-following accuracy
Integrate frontier AI models such as OpenAI, Anthropic Claude, and Google models while helping define long-term AI architecture strategies
Design & Development
Build and maintain high-performance backend services using Python and Golang or Java
Develop modern, responsive enterprise applications using React.js and Next.js
Own features end-to-end, from architecture and implementation through deployment and production support
Design scalable distributed systems that are secure, observable, and performant
Drive cloud deployments using AWS, GCP, or Azure with strong CI/CD, Infrastructure as Code (IaC), monitoring, and operational excellence
Quality & Best Practices
Write clean, maintainable, and well-tested code with strong focus on performance, scalability, and reliability
Establish engineering best practices around testing, deployment, observability, and documentation
Continuously evaluate emerging technologies and AI advancements to improve product capabilities
Proactively identify opportunities to improve system performance, engineering productivity, and platform resilience
Requirements
1 year of professional software engineering experience building and operating enterprise-scale software systems
Proven production experience developing AI agent systems involving multi-step reasoning, planning, memory, and tool usage
Strong hands-on experience with Python and either Golang or Java
Production experience with Retrieval-Augmented Generation (RAG), including vector databases, embedding pipelines, hybrid search, and retrieval optimization
Solid frontend development experience using React.js, Next.js, or equivalent frameworks
Strong understanding of distributed systems architecture and software scalability
Hands-on experience building and deploying agentic AI systems using frameworks such as LangGraph, LangChain, LlamaIndex, CrewAI, or equivalent orchestration frameworks
Experience working with vector databases such as Pinecone, Weaviate, Qdrant, pgvector, or similar technologies
Experience deploying, fine-tuning, or optimizing open-source LLMs is highly preferred
Knowledge of AI evaluation methodologies, prompt testing, model benchmarking, and hallucination measurement is a strong advantage
Work Environment
High-Intensity Environment: Fast-paced startup with demanding workload and potential weekend work when needed
Flexible Hours: flexibility is required for project deadlines and global team collaboration
Regional Collaboration: Work closely with colleagues, clients, and partners across Asia
What We’re Looking For
Results-Oriented: Technical decision-making ability considering business impact
Initiative: Self-starter with strong decision-making and execution capabilities
Adaptability: Flexibility to handle changing priorities and requirements
Growth Mindset: Commitment to continuous learning and improvement
Collaboration: Effective communication with diverse, multicultural team members
What We Offer
Competitive salary commensurate with experience, plus performance-based bonus
Meaningful equity participation with ownership in the company's future growth
Direct ownership of an AI-Native enterprise platform powering critical business decisions
Opportunity to work alongside a senior, ambitious, and high-performing engineering team
Learning budget for conferences, courses, certifications, books, and professional development
Modern technology stack and the freedom to make impactful architectural decisions
Significant visibility and measurable impact on products used by enterprise clients across the region
