Software Engineer, Agentic AI
HybridCambridge, England, United Kingdom
Job Summary
Architect, develop, and deploy AI agents and copilots for Roku TV use cases, integrating them with internal systems, tools, and services. Own end-to-end agentic systems from concept to production, including model selection, prompt and context design, retrieval strategies, backend services, and conversational interfaces. Design and implement single-agent and multi-agent orchestration patterns, including handoffs, delegation, and cooperative task execution. Build scalable RAG and context pipelines that provide high-quality grounding for AI systems and keep them aligned with evolving data sources and business logic. Implement tool-calling, function-calling, and MCP-style integrations so agents can safely take actions and interact with the systems around them. Create reusable agent templates, modular components, and paved-path patterns that accelerate adoption across teams and use cases. Establish strong evaluation, observability, and monitoring for conversation quality, task success rate, latency, cost, and overall system performance. Build safeguards that improve production readiness and reliability, including testing pipelines, controlled rollouts, drift detection, and mechanisms that prevent error amplification in multi-step workflows. Prototype quickly, run experiments, and translate successful ideas into durable, scalable software solutions. Partner closely with engineering, product, QA, infrastructure, and cross-functional teams to deliver meaningful business and customer outcomes.
Required Qualifications
- Bachelor's or master's degree in Computer Science, Computer Engineering, Electrical Engineering, Data Science, or a related technical field.
- 2+ years of experience in software engineering, AI/ML engineering, backend development, or adjacent domains, with strong software engineering fundamentals and the ability to build production-grade systems.
- Strong proficiency in Python, plus experience with C/C++ or another systems language.
- Hands-on experience with LLM-based systems, including prompt design, retrieval, tool use, memory handling, and agent orchestration patterns.
- Experience building and maintaining RAG pipelines, agent frameworks, MCP servers or equivalent function-calling architectures, and conversational interfaces.
- Familiarity with cloud platforms, REST APIs, containerization, and modern deployment environments.
- Experience with observability, evaluation, experimentation, and feedback loops for AI systems in production.
- Ability to work independently, manage ambiguity, move quickly, and deliver incrementally in a fast-paced environment.
- Excellent communication skills, sound engineering judgment, and a collaborative working style.
Desired Qualifications
- Experience with multi-agent frameworks or orchestration systems such as LangChain, AutoGen, or Semantic Kernel.
- Experience with video, audio, TV, or edge-device environments, especially where latency, cost, and hardware constraints matter.
- Familiarity with ML/DL frameworks such as PyTorch or TensorFlow.
- Research experience, paper implementation experience, or a habit of applying emerging GenAI techniques pragmatically to real problems.
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