Software Engineer

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