Artificial Intelligence Engineer

AI & LLM Application Skills LLM application development: Hands-on experience building production applications powered by LLMs. Must go beyond API calls — RAG pipelines, chain-of-thought reasoning, structured output parsing, multi-step workflows. Candidates who have only fine-tuned models or only called a single provider’s API do not qualify. Model-agnostic design: This is a sovereign AI system. The candidate must design against standardized API interfaces (OpenAI-compatible, LiteLLM, or equivalent abstraction layers), not couple to any single provider. Must understand model routing, fallback strategies, and how to build systems that can swap underlying models without application-layer rewrites. Experience limited to a single commercial API (OpenAI, Google, Anthropic) without abstraction is insufficient. Agentic system design: Demonstrated experience designing multi-step AI systems where the model makes decisions about what to do next. This could be via LangGraph, CrewAI, AutoGen, custom agent loops, or any framework — the underlying patterns (ReAct, plan-and-execute, reflection) matter more than the tool. Prompt engineering depth: Can demonstrate iterative prompt development for complex tasks. Understands few-shot, chain-of-thought, XML/structured prompting, and the behavioral differences between model families and sizes. Critically, understands that prompt strategies must adapt when moving between frontier and smaller OSS models.

Python Engineering Production Python: Strong async Python with FastAPI or equivalent framework. Comfortable with Pydantic for data validation, SQLAlchemy for data access, and structured logging (structlog). Writes clean, testable, well-documented code with proper type hints. This is a software engineering role that builds AI systems — not a data science role that happens to write Python. Safeguards for hallucinated tools, loops, partial completion, and unsafe actions. Understands async trade-offs, batching, streaming, and latency accumulation Engineering Qualities Works within existing systems: The candidate joins a substantial existing codebase and architecture. They must be comfortable reading, understanding, and extending code they did not write — not lobbying to rewrite it. Production mindset: Thinks about error handling, retry logic, graceful degradation, observability, and security as first-class concerns. Understands that agentic autonomy creates new failure modes that must be anticipated. Clear communicator: Can explain technical trade-offs to non-technical stakeholders. Can write clear design documents. Can articulate why an agentic approach is or is not appropriate for a given problem. Company Overview At SBS, we’re more than just a technology company; we’re a global fintech partner helping banks and financial institutions transform, innovate, and grow. With over 5,000 employees worldwide and clients in more than 80 countries, our solutions power everything from digital banking and lending to payments and core banking systems. As part of 74Software, we’re backed by a group of leading software companies delivering mission-critical solutions worldwide. Our focus is on delivering long-term value, leveraging cutting-edge technology, and fostering strong client partnerships. Join us and be part of a collaborative, forward-thinking team shaping the future of finance. Why SBS? At SBS, we’re committed to supporting our employees in every aspect of their lives, from health and wellbeing to financial security and lifestyle perks. We offer benefits that help you thrive at work and beyond, including health coverage, retirement plans, paid time off, flexible work options, career development, competitive pay, and global culture perks. Equal Opportunity Employer We are committed to providing equal opportunities and ensuring a fair and inclusive recruitment process. We do not discriminate on the basis of age, disability, gender, sexual orientation, race, religion, or any other protected characteristic.