As an AI Engineer, you’ll play a key role in designing, building and operating AI powered, agentic features that are used by real customers and colleagues at scale. You’ll work hands-on with large language models, AWS AgentCore based patterns and modern engineering frameworks to turn ideas into reliable, production ready systems that deliver measurable value. This role sits at the intersection of engineering, product and data, requiring strong technical execution and thoughtful collaboration across teams.

This is a practical, delivery focused role where shipping matters. You’ll be involved throughout the lifecycle, from identifying high value opportunities for agentic automation, through prototyping and integration, to monitoring and improving systems once they are live. You’ll balance experimentation with robustness, ensuring solutions are scalable, secure and cost effective while meeting real user needs, including safe and reliable access to internal APIs, platforms and external services.

We welcome applicants from diverse backgrounds who enjoy building, learning and iterating in collaborative teams. You are someone who is comfortable navigating uncertainty, making evidence based decisions and refining approaches as models, tools and requirements evolve. You combine curiosity with pragmatism, helping the team make sensible choices around performance, reliability, privacy and risk, ensuring AI agents are applied thoughtfully to solve meaningful problems.

Key Responsibilities

• Agentic Feature Design & Delivery: Design, build and run AI powered agent experiences, translating product ideas into reliable, scalable production systems that deliver measurable impact.

• AWS AgentCore Integration & Orchestration: Build and operate agent runtimes and orchestration using AWS AgentCore, enabling robust tool use, workflow execution and safe interaction with internal and external systems.

• LLM Integration & System Architecture: Integrate LLMs into existing applications and services, shaping backend architectures and APIs that balance performance, cost, security and maintainability, including patterns for agent to service communication.

• Tooling and API Connectivity: Design and implement secure, resilient tool interfaces that allow agents to interact with our APIs, platform capabilities and other services, with strong controls around authentication, authorisation, rate limiting and failure handling.

• Agentforce Interoperability: Enable integration patterns between AWS based agent systems and Agentforce where required, supporting consistent user journeys, capability handoff and shared governance across platforms.

• Prompt Engineering & Agent Optimisation: Develop, test and refine prompt and agent strategies to improve accuracy, safety, latency and cost efficiency across different use cases, including tool selection, planning and response quality.

• Hands-On Engineering: Build and maintain backend services and APIs using TypeScript and modern frameworks, contributing clean, well documented and maintainable code aligned with engineering best practice.

• Evaluation & Monitoring for Agents: Define and implement evaluation approaches for agentic systems, including logging, traces, metrics and experimentation to continuously improve quality, reliability and tool effectiveness in production.

• Scalable Agent Patterns: Contribute to shared approaches, architectural patterns and standards for building and governing agents across the platform including reusable tools, memory patterns, observability and rollout practices.

• Risk, Privacy & Cost Awareness: Make informed engineering decisions that consider data privacy, model risk, operational resilience and commercial constraints, including safe handling of sensitive data and guardrails for tool use.

Knowledge, skills and experience required

Our tech stack includes Typescript (Node.js and React), AWS, Kubernetes, DataDog, GraphQL, PostgreSQL, Mongo, and Kafka.

We’re looking for someone who brings:

• Strong software engineering foundations, with hands-on experience building, shipping and operating scalable, production-grade systems.

• Proven experience working with modern JavaScript and TypeScript stacks, including Node.js and associated backend frameworks, and confidence contributing to clean, maintainable codebases.

• Strong practical experience building agentic systems in AWS, with demonstrable capability using AWS AgentCore to design, orchestrate and operate production agents, including tool execution, workflow patterns and runtime concerns.

• Working knowledge of Agentforce concepts and integration approaches, with the ability to design interoperability patterns between agent platforms and enterprise services.

• Practical experience integrating large language models into real applications using APIs such as OpenAI, Anthropic or similar, with an understanding of prompt design, evaluation and operational trade-offs.

• Confidence designing and working with APIs and backend services, including RESTful architectures and integration patterns that support reliability and scale, with particular strength in designing tool interfaces for agent access.

• Familiarity with cloud-native environments and production tooling, including containerisation, monitoring and deployment practices, ideally within AWS based ecosystems.

• Experience working with data stores such as PostgreSQL, MongoDB and or vector databases, with an understanding of how data design supports AI driven and agent driven use cases, including retrieval patterns and structured tool outputs.

• Strong understanding of distributed systems concerns relevant to agents, including retries, idempotency, timeouts, circuit breaking, asynchronous workflows and safe degradation.

• Ability to reason about cost, latency, privacy and risk when designing agentic systems, including governance for tool permissions, data handling, prompt and output safety and operational resilience.

• Strong problem solving skills and attention to detail, with a mindset oriented toward iteration, evidence and continuous improvement.

• Ability to communicate complex technical concepts clearly and simply to a range of audiences, from engineers to product partners and non-technical stakeholders.

• Curiosity and adaptability, with a genuine interest in staying current with emerging AI agent tools, techniques and best practices, applying them thoughtfully rather than reactively.

• A collaborative approach and empathy for users and teammates, contributing positively to a team environment and shared ownership of outcomes.

We encourage applications from people who want to grow into this role and welcome those who bring diverse perspectives, career paths, and experiences.