📈 Who We Are:
We are rebuilding the energy transaction, making it transparent and fair.
Our goal is to put power back where it belongs, in the hands of customers and to take on one of the most critical problems of our century, access to low cost electricity.
tem exists to fix a broken global energy market that’s long favoured legacy operators, intermediaries, and opaque pricing. Today’s electricity system was not designed for rapid decarbonisation, AI-driven efficiency or fair access for the actual users - businesses and generators.
We’ve built the first AI native transaction infrastructure to reinvent how electricity is bought, sold and priced. Our technology is designed to cut out the inefficient fees, automate complex market flows, and bring transparency and fairness to energy transactions at scale.
In late 2025, after extraordinary growth, we closed a $75 million Series B - led by Lightspeed Venture Partners with participation from Albion, Atomico, Allianz, Hitachi Ventures,, Hitachi Ventures, Schroders Capital and others - positioning us for global expansion, deeper product innovation and category leadership.
We’re scaling internationally and building toward a future where AI-driven infrastructure is foundational to electricity markets worldwide.
Since launch, our modern utility product, known as RED, has already facilitated thousands of business customers and billions in energy transaction value, proving that modern software and AI can transform an industry built on legacy systems.
At tem, we’re not just building another energy company, we’re rearchitecting market infrastructure so that transparency, efficiency and sustainability become the default, not the exception.
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.
Must-Haves:
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.
Desirable:
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 £129,500 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.
tem