Senior AI Engineer (Contractor, Full-Time)

We’re Altura, an ambitious SaaS startup.

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.

We’re building the first AI-powered Agentic Virtual Bid Management Assistant, designed to automate the entire bid lifecycle. With big ambitions and a fast-growing team across Amsterdam and London, we’re just getting started.

If you value innovation, enjoy high ownership, and want to shape the AI backbone of a Series A SaaS company, we’d love to talk.

TL;DR

As a Senior AI Engineer (Contractor), 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 freedom to experiment: Claude Code, Cursor, Copilot, and new frontier models the day they drop. If something meaningfully advances the state of the art, we use it.

You’ll drive high-impact AI initiatives end-to-end:

• Discovery and greenfield prototyping
• Model evaluation and multi-model strategy
• 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

Design and deliver an agentic layer and a rich context graph that automates complex work with deep integration into 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 and online metrics
• Gold sets and regression tests
• Human review loops
• A/B experiments

Operationalize LLMOps:

• Deployment patterns
• Observability and monitoring
• Incident response
• Performance and cost optimization (latency, throughput, token spend)

Build guardrails & security:

• Prompt-injection defenses
• Data-exfiltration prevention
• Tool permissions and action constraints
• Safe handling of sensitive data

Establish engineering standards:

• Reference implementations
• Reusable libraries
• Review practices
• Documentation that accelerates the team

Mentor and influence:

• Raise the bar on system design and code quality
• Align multiple teams on outcomes and timelines
• Act as a technical force multiplier

What we’re looking for

Minimum qualifications

• Extensive experience in AI/ML software engineering with multiple production launches
• Strong software engineering fundamentals (system design, testing, reliability, APIs)
• Proven experience with LLM application patterns (context engineering, embeddings/vector search, structured outputs, prompt design)
• Hands-on experience building evaluation and monitoring systems for model quality in production
• Comfortable in cloud environments (Azure), containers, CI/CD, and modern observability
• Excellent cross-functional communication skills — you turn ambiguity into plans, tradeoffs, and shipped outcomes

Nice to have

• Experience optimizing inference (caching, batching, routing, quantization)
• Experience serving or fine-tuning open-source models
• Experience building internal AI platforms (evaluation harnesses, prompt/version management systems)

What success looks like in 90–180 days

• Delivery of AI-native capabilities aligned with product goals and risk constraints
• A repeatable evaluation and release process that prevents regressions and enables fast iteration
• AI systems in production with monitoring, guardrails, and measurable business impact
• Clear technical standards that elevate the entire engineering organization

What we offer

• Long-term contractor engagement at competitive market rates
• High-impact role shaping the AI backbone of a Series A SaaS company
• Full ownership and technical influence
• Flexible remote work setup
• Occasional travel to Amsterdam for in-person collaboration
• Modern tooling and the freedom to experiment with frontier AI systems