OutSystems is looking to solve the problem of enterprises struggling with the chaos and lack of governance in adopting AI tools. They aim to provide a platform that enables customers to build and deploy AI-powered applications and agents securely, scalably, and with governance, thereby reducing manual work, streamlining operations, and accelerating impact.
Requirements
- 7+ years in software development, with 2+ years in AI/ML engineering or AI agent systems.
- Strong C-Sharp (.NET Core) skills; proficiency in Python or Java is a plus.
- Expertise in AWS cloud services (e.g., Lambda, ECS/EKS, S3, DynamoDB, Bedrock, SageMaker).
- Proficient with Kubernetes for deployment, scaling, and orchestration of AI workloads.
- Hands-on experience with AI agent frameworks (e.g., LangChain, Semantic Kernel, AutoGen) and agent communication standards (MCP, A2A).
- Knowledge of LLM prompt engineering, context management, vector search, and embedding pipelines.
- Mastery of continuous delivery and automated testing techniques, including AI model validation strategies.
Responsibilities
- Design, implement, and maintain AI-powered low-code platform capabilities enabling customers to build and deploy AI agents at scale.
- Architect and optimize agent orchestration pipelines, integrating with AWS services, Kubernetes, and C-Sharp-based microservices.
- Develop solutions leveraging LLMs, AI agent frameworks, and autonomous agent patterns (e.g., task planning, tool use, memory).
- Implement and maintain secure, high-performance APIs for agent execution, communication, and interoperability.
- Build reusable, configurable components to accelerate customer-built AI agents through the low-code platform.
- Ensure high availability, low latency, and observability across AI agent services.
- Integrate AI agent workloads with AWS data services, messaging systems (Kafka/NATS), and event-driven architectures.
Other
- Lead individual contributor responsible for owning complex AI agent platform components, delivering scalable and secure AI-powered low-code solutions, and mentoring other engineers.
- Operates with high autonomy, influences technical direction within the team, and ensures production-ready quality in AI-driven features.
- Availability to participate in an on-call rotation
- Act as a technical mentor, driving AI engineering best practices, knowledge sharing, and innovation across teams.
- Serve as last-line incident responder for complex AI platform issues, participating in the on-call rotation.
