AI Engineer

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.

POSITION SUMMARY:

Our team is becoming an AI-native decision-intelligence function. We're hiring an AI Engineer to design and build intelligent experiences on top of the Data & Intelligence Foundation — agentic workflows, natural-language query, automation, and programmatic access patterns. You'll do more than experiment with AI tools. You'll ship reliable, secure, governed AI capabilities that let stakeholders reach trusted insights without depending only on static dashboards. The ideal candidate blends AI application development with enterprise data-governance awareness.

WHAT YOU WILL BE DOING:

• Design AI-native experiences for interacting with data via natural language, agents, assistant-style interfaces, and programmatic/CLI access.

• Build prototypes and production workflows for KPI lookup, report-health checks, quality validation, insight routing, and stakeholder self-service.

• Partner with Data Engineers to ground AI experiences in trusted semantic models and governed data assets.

• Work with Business Analysts to encode business context, metric interpretation, ontology, and guardrails into AI experiences.

• Support AI-native skilling and engineering practices, including human-in-the-loop needs and capability gaps.

• Drive automation opportunities such as reporting automation, alert/response, validation, and insight routing.

• Apply responsible AI, security, entitlement, and governance principles throughout.

• Define reusable architecture patterns for AI-enabled decision intelligence.

MINIMUM QUALIFICATIONS:

• Must have recent atleast 2 years of hands-on AI/GenAI project experience.
• Practical hands-on experience building or contributing to AI/GenAI solutions is required; candidates should demonstrate real project involvement beyond simply listing AI tools or frameworks.
• Strong practical experience with LLM applications, RAG, agents, prompt engineering, AI workflows, model integration, evaluation, and production deployment should be prioritized.
• Experience with the Microsoft technology stack (e.g. .NET/C#, Azure, Azure OpenAI, Microsoft Fabric).

• Data engineering skills are a big plus — dimensional modeling (star and snowflake schemas), ETL pipelines, and working with big data.

• Familiarity with enterprise data platforms and semantic layers.

• Experience designing AI systems that are grounded, explainable, permission-aware, and aligned with governed data sources.

• Standard engineering practice: Git, CI/CD, testing, logging, monitoring, and deployment.

• A solid software engineering foundation — system design, data structures, concurrency, error handling, and building services that are reliable in production. You treat AI systems with the same engineering rigor as any other software you ship.

• Strong programming skills, ideally in Python and/or TypeScript/C#. You're comfortable working close to the metal — for example, implementing a tool-calling loop yourself rather than depending on a framework to handle it for you..

• Practical experience building AI applications, agents, assistants, or LLM-integrated workflows, and the ability to clearly explain what you built, the decisions you made, and what you'd do differently next time.

• A real grasp of the fundamentals beneath the frameworks: how APIs, backend services, and orchestration fit together; how prompts and context are structured and managed within a model's limits; and how tool/function calling works.

• The ability to debug and evaluate AI systems — to figure out why a model's output is wrong, and to measure whether a change genuinely improved things rather than relying on gut feel.

• Awareness of cost, latency, and reliability trade-offs, and the judgment to choose the simplest approach that solves the problem well.

• Good instincts for matching the technique to the problem — retrieval, fine-tuning, prompt engineering, or plain function calling — based on what the work actually needs.

• Occasional infrequent in person activity may be required

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, national origin, disability status, genetics, veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state, or local laws. This policy applies to all terms and conditions of employment, including recruiting, hiring, and the full employee lifecycle up through and including termination.