Software Engineer, AGI Platform

1 мес. назад

USAMiddle

aisoftware engineeringmachine learning

Develop AI-native digital workers for enterprise-scale intelligent systems, focusing on lending and due-diligence workflows.

Условия

What draws people to is the opportunity to build something truly foundational.
We are at the beginning of a new era  — one where enterprise systems will no longer be static tools, but  dynamic collaborators  that learn, reason, and evolve alongside the people who use them. At , you’ll help build a platform that redefines how work happens in the  AGI era .
brings together vision, deep technology, and purpose . This is not about experimenting with AI features; it’s about turning the promise of  AGI  into  practical, auditable, and human-aligned systems that enterprises can trust and rely on at scale. The work here directly impacts productivity, efficiency, and decision-making in complex, real-world environments.
If you’re motivated by building systems that matter — systems that combine intelligence with responsibility — offers the chance to do that work at a deeper level, with real ownership and lasting impact.

Другое

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As a Software Engineer, AI Platform, you will help design, build, and operate core services and product capabilities for ’s enterprise platform. This is a software engineering role with strong exposure to modern AI systems, including LLM-powered services, agentic workflows, retrieval systems, evaluation pipelines, and production-grade AI infrastructure.
You will work across backend services, APIs, platform components, and product workflows that enable AI-driven enterprise applications to run reliably in production. You will collaborate closely with research engineers, product managers, designers, and other software engineers to turn AI concepts into scalable, secure, and operable systems.
Design and develop scalable backend services, APIs, and platform components for enterprise AI applications.
Build reliable systems for workflow execution, orchestration, observability, and evaluation.
Contribute to cloud-native infrastructure and service architecture with strong focus on performance, reliability, and maintainability.
Integrate LLMs, retrieval pipelines, agent frameworks, and related AI services into production-grade product experiences.
Build and improve services that support prompt execution, tool use, knowledge retrieval, memory, and evaluation workflows.
Help operationalize AI systems with proper monitoring, traceability, governance, and scalability.
Work closely with research and AI engineers to productionize experimental capabilities.
Partner with product, design, and architecture teams to translate complex requirements into modular and scalable implementations.
Contribute to technical design discussions and help shape platform direction.
Write clean, testable, maintainable code.
Improve system operability through strong testing, logging, alerting, and automation.
Contribute to code reviews, technical standards, and engineering best practices.
3+ years of experience designing and building production software systems.
Strong software engineering fundamentals in one or more of: Java, Python, Go, JavaScript/TypeScript, or C++.
Experience building backend services, APIs, and distributed systems.
Experience with cloud platforms, containers, and modern deployment practices.
Strong understanding of software quality, testing, debugging, and operational reliability.
Ability to work in a fast-moving, cross-functional environment and turn ambiguous requirements into working systems.
Experience with AI/ML-enabled products or platforms.
Familiarity with LLMs, retrieval-augmented generation, prompt workflows, or agent frameworks such as LangChain, LlamaIndex, CrewAI, or AutoGen.
Exposure to MLOps, observability, evaluation frameworks, or experimentation platforms.
Experience with knowledge graphs, ontology-driven systems, or enterprise search and retrieval is a plus.
Experience with Kubernetes, Docker, infrastructure as code, and cloud-native architecture.