Applied AI Engineer - (Europe or UK)

SIVAD Consulting; United Kingdom; Remoto; GBP 83.000 - 125.000; Tempo pieno

Descrizione del lavoro

SIVAD Consulting is seeking an Applied AI Engineer to help design and build agentic systems that operate in production across Europe and the UK. The role emphasizes autonomous work on memory, context management, tool-calling, and orchestration, with a focus on reliability and scalable workflows.

You will push the boundaries of how LLMs integrate into software development, create end-to-end evaluation pipelines, and collaborate with product and operations teams.

Competenze

• Proven software engineering track record from idea to production.
• Hands-on experience building AI or agentic systems in production.
• Experience addressing reliability, latency, context management, failure modes, evaluation, and observability.
• Strong understanding of agents, tool use, structured outputs, context management, orchestration, evaluation, and feedback loops.
• Experience designing workflows with coding agents and subagents and mechanisms to verify outputs.
• Ability to decide when to use LLMs, deterministic software, human intervention, or a mix of approaches.
• Proficient in TypeScript/Node.js or Python with a TS-first mindset.
• Excellent communication in English; startup mindset for fast-paced environments.

Mansioni

• Design and build core primitives for agentic systems, including memory, context management, tool-calling, orchestration, and feedback loops.
• Move toward reusable infrastructure enabling new workflows quickly and reliably.
• Develop evaluation frameworks to understand agent performance and reasons for success or failure.
• Integrate testing, tracing, debugging, and evaluation into the engineering process.
• Create systems to assess agentic workflows before production deployment.
• Advance use of LLMs to build software itself.
• Design workflows where coding agents and subagents explore repositories, implement changes, review architecture, and run evaluations.
• Promote agentic workflows in day-to-day development; ensure human coordination only when needed.
• Design architectures where agents, tools, deterministic software, and humans collaborate effectively.
• Decide when problems are better solved by LLMs vs traditional software; bridge complex workflows with engineering teams.
• Collaborate with operations and product teams to automate agency-related workflows and produce reliable production systems.
• Help define architectural patterns for agentic systems as the company scales.
• Join as an early core member with influence over technical approach and standards.

Conoscenze

Software engineering

Agentic systems

LLMs workflows

TypeScript/Node.js

Python AI

Observability

Reliability/Latency

English fluency

Autonomy

Descrizione del lavoro

Applied AI Engineer - (Remote) (Europe or UK - Required) 100k - 150k Euro

Responsibilities

• Design and build the core primitives behind our agentic systems, including memory, context management, tool-calling, orchestration, and feedback loops
• Move us from one-off AI solutions toward reusable infrastructure where new workflows can be introduced quickly and with predictable reliability
• Build the evaluation framework that allows us to understand how our agents perform and why they succeed or fail
• Make testing, tracing, debugging, and evaluating AI systems as fundamental to our engineering process as unit testing traditional software
• Develop the systems that allow us to confidently assess an agentic workflow before deploying it into production
• Push forward how we use LLMs to build software itself
• Create workflows where coding agents and specialized subagents can explore repositories, implement changes, review architecture, check conventions, run evaluations, and iterate with minimal human coordination
• Use agentic engineering workflows extensively in your own day-to-day development
• Design systems where specialized agents, tools, deterministic software, and humans work together effectively
• Understand when a problem should be solved with an LLM, when traditional software is the better solution, and when multiple coordinated agents can materially improve the outcome
• Act as the bridge between complex operational workflows and engineering
• Work closely with our operational and product teams to understand how work actually happens across acquired agencies, identify the highest-leverage opportunities for automation, and turn them into reliable production systems
• Help define the architectural patterns we use for agentic systems as the company scales
• You won't be joining as engineer #20 on an established AI platform. You will be an early core member of the team with significant influence over our technical approach, tooling, and engineering standards

Requirements

• Strong software engineering background with experience independently delivering complex systems from idea through to production
• Hands-on experience building AI or agentic systems that have operated in production
• Experience dealing with real-world AI challenges such as reliability, latency, context management, failure modes, evaluation, and observability
• Strong understanding of agents, tool use, structured outputs, context management, orchestration, evaluation, and feedback loops
• Advanced practical use of modern LLMs - not simply using ChatGPT or Claude occasionally, but understanding how to build reliable workflows around probabilistic systems
• Experience using coding agents and agentic development workflows as part of your own engineering process
• Experience decomposing complex engineering tasks across agents or specialized subagents and designing mechanisms for them to verify and improve their outputs
• Strong architectural judgment and ability to decide when to use LLMs, deterministic software, human intervention, or a combination of approaches
• Experience with TypeScript / Node.js, or strong experience building AI systems in Python with the ability and willingness to apply that knowledge in a TypeScript-first environment
• High autonomy, ownership, and comfort making decisions under ambiguity
• Strong product judgment and ability to connect technical decisions to operational and business outcomes
• Strong communication skills and fluency in English
• Startup mentality: resilience, adaptability, and ability to thrive in a fast-paced environment