AI Engineer

Responsibilities

The AI Engineer will design, develop, and deploy production-grade AI applications, focusing on Agentic AI, multi-agent systems, and RAG pipelines. They will also manage cloud-based AI solutions, backend API development, and ensure system reliability through monitoring and CI/CD practices.

Requirements

Candidates must have a bachelor's degree in a relevant field and at least 4 years of experience in software or AI engineering. Strong proficiency in Python, experience with LLM integration, and practical knowledge of cloud deployment and containerization are required.

Skills

• Python
• Agentic AI
• Multi-agent systems
• RAG
• LLM engineering
• FastAPI
• Cloud computing
• AWS
• Azure
• Google Cloud
• Docker
• Kubernetes
• CI/CD
• Vector databases
• Prompt engineering
• Backend development

About this role

Overview
WHO WE ARE:
Beyondsoft is a leading mid-sized business IT and consulting company that combines modern technologies and proven methodologies to tailor solutions that move your business forward.Our global head office is based in Singapore, and our team is made up of a diversely talented team of experts who thrive on innovation and pushing the bounds of technology to solve our customers’ most pressing challenges.When it comes time to deliver, we set our sights on that sweet spot where brilliance, emerging technologies, best practices, and accountability converge. We have a global presence spanning four continents (North America, South America, Europe, and Asia). Our global network of talent and customer-centric engagement model enables us to provide top-quality services on an unprecedented scale.
WHAT WE’RE ABOUT:
We believe that collaboration, transparency, and accountability are the values that guide our business, our delivery, and our brand. Everyone has something to bring to the table, and we believe in working together with our peers and clients to leverage the best of one another in everything we do. When we proactively collaborate, business decisions become easier, innovation is greater, and outcomes are better.
Our ability to achieve our mission and live out our values depends upon a diverse, equitable, and inclusive culture. So, we strive to foster a workplace where people have the respect, support, and voice they deserve, where innovative ideas flourish, and where people can unleash their brilliance. For more information regarding DEI at Beyondsoft, please go to https://www.beyondsoft.com/diversity/.
ADDITIONAL REQUIREMENT FOR REMOTE POSITIONS:
For remote positions, all candidates must complete a video screen with our corporate recruiting team.
Responsibilities
POSITION SUMMARY:
We are seeking a hands-on AI Engineer to design, develop, and deploy production-grade AI applications, with a focus on Agentic AI, multi-agent systems, Retrieval-Augmented Generation (RAG), and cloud-based AI solutions. The ideal candidate combines strong Python and backend engineering skills with practical experience building AI-powered applications, integrating LLMs with enterprise data, and deploying scalable, secure, and reliable solutions in production environments.
WHAT YOU WILL BE DOING:
Agentic AI & Multi-Agent Systems: Design and implement AI agents and multi-agent workflows using frameworks such as LangGraph, CrewAI, LangChain, or similar technologies. Develop solutions involving tool calling, task orchestration, workflow automation, and agent collaboration.
RAG & LLM Engineering: Build and optimize RAG pipelines, including document processing, chunking, embeddings, vector search, hybrid retrieval, reranking, and context management to improve response quality.
Python & Backend Development: Develop scalable backend services and APIs using Python, FastAPI, or equivalent frameworks. Integrate AI capabilities with databases, enterprise applications, and external systems.
Cloud AI Solutions: Build and deploy AI applications using cloud platforms such as AWS, Azure, or Google Cloud. Integrate managed AI services and model APIs based on project requirements.
Production Deployment: Deploy, monitor, and maintain AI applications using Docker, Kubernetes, CI/CD pipelines, and cloud-native services. Ensure reliability, scalability, and maintainability beyond the proof-of-concept stage.
AI Evaluation & Optimization: Evaluate LLM outputs, retrieval quality, latency, and cost. Implement automated testing, tracing, observability, guardrails, and human-in-the-loop controls.
Data & Model Integration: Work with LLMs, embedding models, vector databases, and structured and unstructured data sources. Apply prompt engineering, model selection, and fine-tuning techniques where appropriate.
Security & Reliability: Implement secure API integrations, access controls, data protection, and responsible AI practices.
Cross-Functional Collaboration: Partner with product, engineering, and business teams to translate requirements into effective AI solutions and measurable business outcomes.
Qualifications
MINIMUM QUALIFICATIONS:
Bachelor’s degree in Computer Science, Software Engineering, AI, or a related field, or equivalent practical experience.
4+ years of experience in software engineering, AI/ML engineering, or backend development.
Strong hands-on Python development experience, including API development with FastAPI or similar frameworks.
Demonstrated experience building Agentic AI applications, multi-agent workflows, or LLM-powered automation.
Practical experience developing RAG solutions using embeddings, vector databases, and retrieval techniques.
Experience integrating LLMs and AI services into backend applications and enterprise systems.
Experience deploying applications to a cloud environment such as AWS, Azure, or GCP.
Familiarity with Docker, Kubernetes, CI/CD, application monitoring, and production troubleshooting.
Strong problem-solving skills and the ability to deliver maintainable, production-ready code.
PREFERRED QUALIFICATIONS:
Experience with LangGraph, CrewAI, LangChain, Semantic Kernel, or similar agentic frameworks.
Experience with managed AI services such as AWS Bedrock, Azure OpenAI, Azure AI Foundry, or Google Vertex AI.
Familiarity with PostgreSQL, Redis, Elasticsearch, Cosmos DB, or other vector and data storage technologies.
Experience with LLM fine-tuning techniques such as LoRA or QLoRA.
Knowledge of inference optimization, model quantization, GPU utilization, or CUDA.
Experience with AI evaluation frameworks, observability, tracing, guardrails, and production performance optimization.
Familiarity with Go, TypeScript, React, or other technologies used in full-stack application development.
Beyondsoft provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type with regards to race, color, religion, age, sex,...

About Beyondsoft Consulting

IT Services and IT Consulting · 501-1,000 employees · headquartered in Bellevue, Washington