Staff Software Engineer

What you'll do

• Design and build production-grade agentic SDLC workflows from prompt design through tool integration to autonomous execution loops
• Implement RAG pipelines over enterprise knowledge bases (JIRA, Confluence, internal wikis)
• Integrate LLM APIs with proper rate-limit handling, cost governance, and fallback routing
• Build and maintain multi-modal agent tool libraries for JIRA, Confluence, GitHub/Bitbucket, and calendar-aware sprint agents
• Develop front-ends for delivery dashboards with real-time data, drill-down charts and actionable AI insights
• Build backends that aggregate data from internal planning tools and serve them to front-end and agent layers
• Design and maintain database schemas for program metrics, sprint snapshots, and model response logs
• Containerize and deploy services on AWS or Azure using Docker and CI/CD pipelines
• Instrument LLM observability metrics such as latency, token spend, hallucination flags, and user feedback loops
• Maintain version control and A/B testing to iterate on model behavior without redeployment
• Partner with Program Managers, Product Owners, Scrum Masters to translate delivery challenges into agent-addressable requirements
• Document agent designs, API contracts, and RAG architecture decisions in Confluence
• Contribute to Agile COE metrics strategy and ensure data pipelines feeding dashboards are audit-ready

Requirements

• 2+ years hands-on building LLM-powered applications in production
• Proficiency with at least one agent framework: LangChain, LangGraph, AutoGen, CrewAI, or Semantic Kernel
• Practical RAG experience: chunking, embedding, vector stores and retrieval evaluation
• Experience integrating OpenAI, Anthropic, or Azure OpenAI APIs with tool/function calling, structured outputs, streaming
• Design prompt templates, system prompts, and chain-of-thought scaffolding for reliability at scale
• 6-8+ years with Python (preferred) or Java for API and service development
• REST API design and implementation using FastAPI, Flask, Spring Boot, or Node.js/Express
• SQL fluency: query optimisation, schema design, and data modelling across PostgreSQL, MySQL, or Snowflake
• Understanding of async patterns, message queues (Kafka, SQS, RabbitMQ), and event-driven architectures
• Frontend React + TypeScript with hooks, context, and component composition patterns
• Data visualisation with Recharts, Chart.js, or D3 for operational dashboards
• Experience consuming streaming REST or WebSocket APIs for real-time UI updates
• AWS or Azure experience: compute, storage, managed databases
• Docker, container orchestration basics, and CI/CD pipeline ownership
• Monitoring and alerting with CloudWatch, Datadog, or equivalent

Tech stack

Benefits