AI Engineer - Nexus Black

Company Description

IFS is a billion-dollar revenue company with 7000+ employees on all continents. Our leading AI technology is the backbone of our award-winning enterprise software solutions, enabling our customers to be their best when it really matters–at the Moment of Service™. Our commitment to internal AI adoption has allowed us to stay at the forefront of technological advancements, ensuring our colleagues can unlock their creativity and productivity, and our solutions are always cutting-edge.

At IFS, we’re flexible, we’re innovative, and we’re focused not only on how we can engage with our customers but on how we can make a real change and have a worldwide impact. We help solve some of society’s greatest challenges, fostering a better future through our agility, collaboration, and trust.

We celebrate diversity and understand our responsibility to reflect the diverse world we work in. We are committed to promoting an inclusive workforce that fully represents the many different cultures, backgrounds, and viewpoints of our customers, our partners, and our communities. As a truly international company serving people from around the globe, we realize that our success is tantamount to the respect we have for those different points of view.

By joining our team, you will have the opportunity to be part of a global, diverse environment; you will be joining a winning team with a commitment to sustainability; and a company where we get things done so that you can make a positive impact on the world.

We’re looking for innovative and original thinkers to work in an environment where you can #Make Your Moment so that we can help others make theirs. With the power of our AI-driven solutions, we empower our team to change the status quo and make a real difference.

If you want to change the status quo, we’ll help you make your moment. Join Team Purple. Join IFS.

We are seeking an AI Engineer with a builder’s mindset to bring cutting-edge AI agents and workflows into production for IFS Nexus Black. You’ll turn ambiguous customer problems into working prototypes in days/weeks, iterate in the field, and scale the winners into reliable products.

You will work across the stack—prompting, tools, retrieval, evaluation, guardrails, and backend services—collaborating closely with product, design, and data engineering. Expect high autonomy, direct exposure to customers, and a fast loop from idea → demo → production.

Key Responsibilities:

• Rapidly prototype AI agents and guided workflows that solve concrete customer problems; ship thin slices, instrument, and iterate with real usage.
• Design and implement cloud-native backend services that orchestrate prompts, tools, retrieval, and automations; own the path from POC to production.
• Build robust retrieval for LLMs (search/vector pipelines, context assembly, tool selection) in partnership with data engineering.
• Establish evaluation loops: offline/online tests, golden sets, regression checks, and human-in-the-loop review to measurably improve quality and safety.
• Contribute to developer experience: reusable agents/tools, SDKs, templates, and internal documentation that speed up future builds.
• Collaborate with customers and internal stakeholders to frame problems, define success metrics, and translate insights into productizable solutions.
• Lead design discussions and code reviews; mentor teammates and raise the quality bar while keeping momentum high.

4–8+ years as a software/AI engineer, including shipping 0→1 products or features in startup-like environments.

• Strong in Python (and comfortable with Type Script); able to build production services and integrate with external systems/APIs.
• Proven experience taking LLM/agent systems to production (tool use, function calling, planning/exec, retrieval-augmented generation).
• Hands‑on with evaluation (offline/online), prompt engineering, tracing, and observability for AI systems.
• Familiarity with vector databases/search, embeddings, and context/retrieval patterns; pragmatism about when/what to index.
• Solid backend fundamentals (services, queues, data models, CI/CD, cloud) and a bias to automate what you repeat.
• Exce…