Applied AI Engineer –

Sivad Consulting; Greater London; Remoto; GBP 84.000 - 125.000; Tempo pieno

Descrizione del lavoro

SIVAD Consulting seeks an Applied AI Engineer to design and implement agentic systems, with a focus on production-ready workflows and reliable instrumentation. The role emphasizes building reusable infrastructure and tooling to scale AI-enabled software across European/UK contexts.

You will work with memory, context management, tool-calling, and orchestration, shaping how agents and subagents collaborate with humans in complex operational scenarios.

Competenze

• Strong software engineering background with end-to-end delivery to production.
• Hands-on experience building AI/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.
• Advanced practical use of modern LLMs and building reliable workflows around probabilistic systems.
• Experience using coding agents and agentic development workflows.
• Decomposing complex tasks across agents and designing verification mechanisms.
• Judgment to decide when to use LLMs, deterministic software, human intervention, or a mix.

Mansioni

• Design and build the core primitives behind our agentic systems, including memory, context management, tool-calling, orchestration, and feedback loops.
• Move us toward reusable infrastructure for rapid, reliable new workflows.
• Build evaluation framework to measure agent performance and failure reasons.
• Make testing, tracing, debugging, and evaluation fundamental to engineering processes.
• Develop systems to assess agentic workflows before production deployment.
• Push forward how we use LLMs to build software itself.
• Create workflows where coding agents and subagents explore repositories and review architecture.
• Work day-to-day with agentic workflows in development.
• Design systems where specialized agents, tools, deterministic software, and humans collaborate effectively.
• Decide when to apply LLMs vs traditional software or multi-agent coordination.
• Bridge between complex operational workflows and engineering.

Conoscenze

Software engineering

Production AI systems

LLM workflows

Agents & tools

TypeScript/Node.js

Python

Observability

English communication

Startup mindset

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