Functiebeschrijving
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.
Our Tech Stack
AI:
Python
Frontend:
Vue.js and Next.js
Backend:
C# - ASP.NET
Infrastructure:
Azure, GitHub, Linear
What you’ll do (responsibilities)
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.
What we’re looking for (minimum qualifications)
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.
Nice to have
Experience optimizing inference (caching, batching, routing, quantization) or serving open‑source models.
Experience building internal AI platforms (evaluation harnesses, prompt/version management).
What success looks like in 90–180 days
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.
Hiring process
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
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