Senior Software Engineer – AgentOps

Senior Software Engineer AgentOps

About the Role

We are looking for a Senior Software Engineer to design build and scale enterprise-grade agentic AI systems within the AgentOps. This role goes beyond traditional GenAI engineering - focusing on agent orchestration context engineering and production-grade AI systems that automate and transform business workflows through Agents.

You will work at the intersection of LLMs software engineering and platform design owning solutions end-to-end - from ideation to production - while ensuring reliability safety and measurable business impact.

Why Join AgentOps

• Work on cutting-edge agentic AI systems at enterprise scale
• Help build a symbiotic workforce of humans and AI agents
• Solve real business problems across enterprise
• Be part of shaping next-gen AI engineering practices

Key Responsibilities

1. Agentic System Design & Development

• Design and build multi-agent systems and orchestrated workflows for enterprise use cases
• Develop AI-powered solutions using existing SOTA LLMs from hyperscalers and enterprise data sources
• Implement RAG pipelines knowledge retrieval and context-aware reasoning systems
  

2. AgentOps Lifecycle Ownership

• Own full lifecycle: intake design validation deployment monitoring improvement
• Ensure Observability evaluation frameworks and guardrails are in place
  

3. Platform & Integration Engineering

• Integrate AI solutions into Teams web apps and enterprise systems
• Build APIs backend services and orchestration layers for scalable deployments
• Should be well versed with one of the public cloud platform (AWS or Azure or GCP)
  

4. Observability Reliability & Governance

• Implement monitoring (latency accuracy failure modes) and logging pipelines
• Ensure responsible AI practices security and compliance
• Optimize models and workflows for cost performance and scalability
  

5. Innovation & Business Impact

• Partner with product and business teams to identify high-impact agentic opportunities
• Lead PoCs and rapidly scale successful solutions into production
• Drive adoption of agentic workflows across business functions
  

Required Qualifications

• Bachelors/masters in computer science
• 810 years of software engineering experience with strong AI/ML exposure
• Strong technical foundation in Python and modern backend engineering patterns with experience building APIs services and application components
• Experience working with orchestration frameworks such as CrewAI LangGraph AutoGen MAF or equivalent
• Strong working knowledge of retrieval-augmented generation (RAG) embeddings vector search and grounding patterns
• Experience building and deploying cloud-native AI services
• Familiarity with observability and operational tooling such as Application Insights OpenTelemetry Azure Monitor or New Relic or equivalent monitoring platforms
• Good collaboration and communication skills with the ability to work effectively with engineers architects product owners and platform teams
• Strong ownership mindset across the SDLC including design build testing deployment support and continuous improvement
• Experience building production Agentic systems (not just prototypes)
• Exposure to Model Context Protocol (MCP) agent-to-agent (A2A) interaction patterns or similar approaches to context exchange and distributed agent communication.
  

About Pearson

Pearson is the worlds leading lifelong learning company helping millions of learners worldwide achieve their educational and professional goals. Headquartered in London Pearson provides digital learning solutions educational content assessments certifications English language learning and workforce-skilling programs. With a strong focus on innovation technology and learner success Pearson empowers individuals and organizations to thrive in an evolving global economy