At a Glance
- Tasks: Shape and scale AI agent systems with hands-on engineering and strategic influence.
- Company: Join a forward-thinking tech company focused on innovation and collaboration.
- Benefits: Competitive salary, stock options, flexible remote work, and wellness budgets.
- Why this job: Make a real impact by building cutting-edge AI solutions that transform industries.
- Qualifications: Experience in software architecture, AI agents, and strong coding skills required.
- Other info: Dynamic team culture with excellent growth opportunities and a commitment to diversity.
The predicted salary is between 103200 - 155800 ÂŁ per year.
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.
Responsibilities- 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.
- 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.
- 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.
- Experience building internal “paved paths” for agent development (shared libraries, templates, tool interfaces, DX improvements) adopted by multiple teams.
- Experience with agent tooling and orchestration frameworks (e.g., LangGraph, LangChain) and modern evaluation stacks.
- Practical experience with retrieval systems (vector databases, semantic search, chunking strategies, data contracts for trustworthy context).
- Exposure to model operations (multi-provider routing, hosted inference, fine-tuning).
- Experience in regulated or high-correctness domains (energy, fintech, govtech), including auditability and safe degradation patterns.
- Familiarity with workflow orchestration and real-time systems (e.g. pricing engines, complex event-driven workflows).
- Competitive salary - our current band for this role is ÂŁ129,500 or equivalent in local currency. We review salaries twice a year using real-time market data, with transparent, consistent pay for the same role and level.
- Stock Options - everyone on the team has ownership in our mission.
- 25 days holiday + public holidays - Swap public holidays for ones that matter most to you. Plus, get an extra day off for your birthday.
- Remote & flexible working - We’re fully remote with clear core hours, and no internal meetings on Friday afternoons.
- Home working & wellbeing budgets: Up to £1,200 / €1,200 annually to upgrade your remote setup (co-working passes, equipment, etc.). Up to £150 / €150 monthly on anything that supports your wellbeing - from therapy to gym memberships to meditation apps.
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.
We welcome applications from people of all backgrounds, experiences, and identities, including those that are traditionally underrepresented in the tech and energy sectors. 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.
Senior Staff Engineer - Agent Platform employer: tem
Contact Detail:
tem Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Staff Engineer - Agent Platform
✨Tip Number 1
Network like a pro! Reach out to folks in your industry on LinkedIn or at meetups. A friendly chat can lead to opportunities that aren’t even advertised yet.
✨Tip Number 2
Prepare for those interviews! Research the company, understand their products, and think about how your skills align with their needs. We want you to shine!
✨Tip Number 3
Show off your projects! Whether it’s a GitHub repo or a personal website, having tangible examples of your work can really set you apart from the crowd.
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen by the right people. Plus, we love seeing candidates who are proactive!
We think you need these skills to ace Senior Staff Engineer - Agent Platform
Some tips for your application 🫡
Tailor Your Application: Make sure to customise your CV and cover letter to highlight how your experience aligns with the role. We want to see how you can contribute to our Agentic layer, so don’t hold back on showcasing relevant projects!
Showcase Your Technical Skills: When detailing your experience, focus on your hands-on engineering skills and any architectural depth you've got. We’re looking for someone who can design complex systems, so share examples that demonstrate your expertise in building AI agents in production.
Be Clear and Concise: Keep your application straightforward and to the point. Use bullet points where possible to make it easy for us to see your key achievements and skills. Remember, clarity is key when discussing your technical experiences!
Apply Through Our Website: We encourage you to submit your application through our website. It’s the best way for us to track your application and ensure it gets the attention it deserves. Plus, it shows you’re keen on joining our team!
How to prepare for a job interview at tem
✨Know Your Stuff
Make sure you’re well-versed in the architectural depth required for this role. Brush up on your experience with complex, stateful distributed systems and be ready to discuss specific examples of how you've designed and evolved these systems in the past.
✨Showcase Your AI Experience
Prepare to talk about your hands-on experience building AI agents in production. Be ready to share insights on best practices, including agent architectures and prompt engineering, as well as any challenges you faced and how you overcame them.
✨Align Tech with Business Goals
Demonstrate your ability to connect technical decisions to business outcomes. Think of examples where your technical choices positively impacted customer experience or business metrics, and be prepared to discuss these during the interview.
✨Ask Thoughtful Questions
During your interviews, especially the culture-add session, ask questions that show you’re genuinely interested in the company’s values and how they align with yours. This is a great opportunity to gauge if the company culture is the right fit for you.