Senior Staff Engineer, tem

• Architectural depth: Proven ability to design and evolve complex, stateful distributed systems spanning APIs, event-driven architectures, data systems, and agentic applications - where domain logic is the primary source of complexity. Proven patterns for high-throughput performance and scaling architecture to support hundreds of thousands of customers, while preventing domain drift
• Proven experience building AI agents in production, not just demos, with a clear understanding of current best practices (agent architectures, tool calling, RAG where appropriate, prompt and context engineering). Ability to run AI/agentic systems reliably in production with observability, incident readiness, and cost controls
• Deep experience with:
• AWS serverless architecture (Lambda, API Gateway, Event Bridge, Step Functions)
• Event-driven systems and asynchronous workflows
• Strong coding skills: deep hands-on experience with a variety of coding languages, and comfortable with a tech-agnostic approach. Familiarity with Python is a must-have
• Agent quality discipline: hands-on experience with evaluations (offline and online), regression testing, safety guardrails, and monitoring for reliability, cost, and drift
• Strong backend and distributed-systems fundamentals: APIs, asynchronous workflows, state management, idempotency, retries, and failure recovery in high-stakes workflows
• Product & business alignment: Demonstrated ability to connect technical decisions to business outcomes and customer experience
• First-principles problem solving: Ability to reason from fundamentals (constraints, incentives, data and system behaviour) to design solutions in complex, high-stakes domains
• If you’re excited about this role but not sure you meet every requirement, we’d still love to hear from you. Your unique perspective could be exactly what we’re looking for

Desirable

• We are looking for a Senior Staff Software Engineer to help shape and scale our Agentic layer at tem
• This role combines deep hands-on engineering with strategic technical ownership and organisational influence
• You will build the foundations that make AI agents production-ready at tem: the core runtime and tooling, the integration interfaces to our systems, and the engineering standards that let teams ship agentic capabilities safely, reliably, and repeatedly
• You will work end-to-end from early pilots to production roll-outs, partnering closely across engineering, product, data, and domain teams to translate real workflows into durable agent-powered systems
• This role requires strong cross-team influence, the ability to align technical design with product and business outcomes, and the judgment to balance rapid delivery with long-term system integrity
• Ship flagship agentic capabilities: Deliver high-impact agentic workflows end-to-end, from discovery through production roll-out, with clear success metrics and fast iteration loops
• Build and operate production-grade agent systems: Design reliable agentic systems that behave predictably under real-world constraints, including latency, cost, data quality, and failure modes, with strong patterns for state management, idempotency, and safe recovery
• Create shared foundations for agent delivery: Develop the core primitives that enable teams to build agents consistently (runtime patterns, tool interfaces, context management, shared libraries) while avoiding one-off implementations
• Establish a pragmatic Agent Development Life Cycle (ADLC): Implement evaluations, guardrails, tracing, monitoring, and release processes so agents can be measured, debugged, and improved continuously
• Integrate ML and LLM components into production workflows: Work with ML/Data teams to productionise models and LLM capabilities with clear contracts, versioning, observability, and safe degradation patterns
• Maintain clear domain boundaries as adoption scales: Define shared semantics for agent tools and data access, preventing domain drift while enabling teams to move quickly
• Collaborate with Platform on infrastructure and developer tooling: Adopt and extend existing CI/CD, DevEx, and observability systems, contributing back where agentic workloads introduce new requirements
• Success measures:
• 3 months: Ship first flagship agentic workflow to production with defined KPI, runbook/on-call ownership, and baseline telemetry (success rate, latency, cost)
• 6 months: Ship additional workflows or expansions and implement lightweight ADLC: evals + guardrails + monitored rollouts + rollback
• 12 months: Prove repeatable capability: 2+ product teams shipping on shared foundations, faster time-to-prod for new agents, and reliability/cost targets consistently met

• Our processes normally take around 2-3 weeks from first call to offer - please let us know about any adjustments to timelines that may be required
• First call with our Talent Team (30 Mins). This is to understand your experience, motivations, and discuss the role in more detail
• Behaviour Interview with our Engineering Managers (60 Mins). This is your chance to really understand the role, the expectations, and ensure alignment on ways of working
• Technical Interviews with the Team (2 x 90 Mins). You’ll meet with potential peers in this session and will discuss technical topics and experiences
• Culture-Add Interview with Stakeholders (45 Mins). The final session will be with two cross-functional stakeholders, and will explore how your values align with ours, and is designed to be a genuine two-way conversation, your chance to understand what it’s really like to work at tem