Software Engineer [SK-20062]

Join a leading technology innovator at the forefront of groundbreaking advancements, where pushing the boundaries of what’s possible is a daily reality. This organization fosters a culture of creativity, collaboration, and technical excellence, dedicated to empowering engineers across the company to build and deliver cutting-edge solutions more efficiently and effectively. Aquent is a proud partner in the search for this role, connecting top talent with groundbreaking opportunities. Are you ready to be a pivotal force in revolutionizing how engineering teams operate? We’re seeking an exceptional individual to dive into the heart of our internal development ecosystem. In this role, you will design, build, and extend a shared platform that integrates state-of-the-art AI agent technology. This isn’t just about writing code; it’s about architecting robust, scalable solutions that enable teams to harness the power of AI without extensive re-architecture. You’ll set new standards for efficiency and intelligent automation, directly impacting developer productivity and the speed of innovation across the entire organization. You will champion extensibility as a core feature, ensuring that new triggers, agents, or tools can be integrated seamlessly without impacting unrelated system layers. You’ll also be deeply empathetic to the developer experience of your platform’s users, focusing on usability and ease of adoption. This role thrives on navigating ambiguity, understanding that agentic systems are inherently non-deterministic and require empirical, adaptive debugging approaches. What You’ll Do • Architect and implement sophisticated agent orchestration systems, including router functions, queueing mechanisms, and agent invocation services. • Seamlessly integrate AI agent capabilities into modern continuous integration/continuous delivery platforms, designing pipeline configuration patterns where agent invocations execute as stages, process context from code changes, produce artifacts, and control subsequent stages based on AI agent outcomes. • Develop and expand a suite of shared, tool-based functions that empower AI agents with versatile capabilities. • Design and implement advanced knowledge bases, leveraging powerful search and storage technologies to ensure AI agents can reason over a comprehensive, shared organizational context rather than isolated prompts. • Implement robust AI guardrails, including input/output filters, sensitive data scrubbing, content moderation, and fine-grained, per-agent permission boundaries, ensuring secure and compliant AI operations by design. • Develop and integrate resource management controls for efficient resource management, encompassing model tiering and intelligent routing via a large language model gateway, semantic caching, and optimized context-window management. • Instrument the entire AI platform with comprehensive observability, including dashboards, audit trails, and detailed trace logging for every agent invocation (input, output, decision, tokens, cost) to ensure compliance, facilitate debugging, and provide deep operational insights. Must-Have Qualifications • 3–7 years of professional experience in software development. • Strong proficiency in Python and its software development kit for building production-grade serverless functions and event-driven services. • Solid experience with cloud-based services, including serverless compute, application programming interface management, messaging queues, event buses, identity and access management, secrets management, and monitoring tools. • Specific experience with AI agent services, action groups, knowledge bases, and guardrails. • Hands-on experience integrating with large language model application programming interfaces, such as those from leading providers or similar platforms. • Familiarity with continuous integration/continuous delivery platforms and best practices. • A strong security mindset, including expertise in least-privilege access, secure secrets handling, input validation, and an awareness of prompt injection and data-leak risks in large language model workflows. • Comfortable with observability principles, including structured logging, metrics, tracing, and writing highly debuggable code for production environments. Nice-to-Have Qualifications • Experience with vector search and Retrieval-Augmented Generation, including vector databases, embeddings, and retrieval evaluation. • Familiarity with financial operations or resource management concepts, such as cost attribution, intelligent model routing, semantic caching, and batch inference. • Experience building developer platforms or internal tooling that other engineers rely on daily. • Familiarity with advanced AI agent frameworks and an understanding of their architectural tradeoffs.