We’re Altura, an ambitious SaaS startup, and we just raised our Series A!
At Altura, we’re making it easier for organisations to win complex deals (tenders and RfPs). With our AI-powered platform, we simplify bid management by turning it into a smooth, strategic process. We connect workflows, automate tasks, and make knowledge accessible, so teams can work more efficiently and effectively.
But we’re not stopping there.
We’re building the first AI-powered Agentic Virtual Bidmanagement Assistant, designed to automate the entire bid lifecycle. With fresh funding, big ambitions, and a fast-growing team, we’re just getting started.
If you value innovation, enjoy working collaboratively, and want to make a real impact, we’d love to have you on board.
Let’s work together!
TL;DR
As a Senior AI Engineer, you’ll join a high-caliber team building the agentic layer that powers Altura’s next evolution. This is not a “plug prompts into an API” role. You’ll design and ship real agentic workflows: context-aware, production-grade systems that sit on top of our proprietary data graph and become a core technical moat.
You’ll work in a small, fast-moving team with full freedom to experiment: Claude Code, Cursor, Copilot, and new models the day they drop. If something advances the state of the art, we’re using it.
You’ll drive high-impact AI initiatives end-to-end:
From discovery and greenfield prototyping
To model evaluation and multi-model strategy
To production rollout, observability, and continuous improvement
Beyond product capabilities, you’ll help shape foundational AI platform components: context engineering, agent orchestration, evaluation frameworks, tone monitoring, and online observability.
No corporate red tape. No endless committees. Just ownership, speed, and real technical influence.
You’ll ship AI that is:
Reliable in production
Scalable across customers
Measurable in impact
Cost-aware by design
And you’ll help define what “great AI engineering” looks like inside a Series A company operating at the leading edge.
AI: Python
Frontend: Vue.js and Next.js
Backend: C# - ASP.NET
Infrastructure: Azure, GitHub, Linear
Design and Deliver an agentic layer and a rich context graph that delivers automation of work with deep integration in our customers knowledge repositories.
Drive architecture & delivery of production LLM/GenAI systems (context engineering, agentic workflows, model evaluations, multi-model strategies).
Define and implement evaluation: offline + online metrics, gold sets, regression tests, human review loops, and A/B experiments.
Operationalize LLMOps: deployment patterns, observability, monitoring, incident response, and performance/cost optimization (latency, throughput, token spend).
Build guardrails & security: prompt-injection defenses, data-exfiltration prevention, permissions for tools/actions, and safe handling of sensitive data.
Establish engineering standards: reference implementations, reusable libraries, review practices, and documentation that accelerates teams.
Mentor and influence: coach engineers, raise the bar on system design and code quality, and align multiple teams on outcomes and timelines.
Extensive experience in AI/ML software engineering (or equivalent), with multiple production AI/ML launches.
Strong software engineering fundamentals (system design, testing, reliability, code review, APIs).
Proven experience with LLM application patterns (e.g., context engineering, output quality, embeddings/vector search, prompt design, structured outputs).
Hands-on experience building evaluation + monitoring for model/system quality in production.
Comfort operating in cloud environments (Azure), containers, CI/CD, and modern observability.
Excellent cross-functional communication: you can translate ambiguity into plans, tradeoffs, and shipped outcomes.
Experience optimizing inference (caching, batching, routing, quantization) or serving open-source models.
Experience building internal AI platforms (evaluation harnesses, prompt/version management).
Delivery of AI native capabilities in our platform, aligned with product goals and risk constraints.
A repeatable evaluation + release process that prevents regressions and supports fast iteration.
AI capabilities shipped with monitoring, guardrails, and measurable business impact.
Recruiter screen (30 min)
Technical deep-dive + system design (60–90 min)
Practical exercise or pairing (60 min) - Fully agentic coding session
Final conversation
Offer
We offer
Work - Work for an AI-build SaaS startup, going scaleup
Time - 40 hours per week ⏱️
Compensation - Competitive salary and Virtual Stock Units (VSUs) 💸
Free - 26 vacation days 🏖️
Tech - All the tools and tech stack you want 🛠️
Flexibility - Work remotely when and how you want. Want to have the Thursday afternoon off and work on Sunday? As long as output is delivered and results are met 🔄
Fun - Tear at the go-kart track or bowl your colleagues out during our company outings, but feel no need to join 🏎️
Development - Budget to develop and spend it on courses you want 💡
Macbook 💻
Hybrid working model - 2 days/week in either our Amsterdam or London office 🏫