Most GenAI never leaves the demo. We hire for the people who get it into production, and into daily use. The Forward Deployed Engineer closes that gap: a field engineer who builds GenAI applications (agents, RAG pipelines, copilots) and makes sure they get adopted, embedded in daily workflows, and deliver measurable value. You quickly grasp a client’s operational challenges, design a tailored response, deploy it, and bring teams along in the transformation. 
You will operate at the intersection of Data Science, ML/Platform Engineering, and client delivery, helping customers find the right level of sophistication, semantic search, RAG, agents, or fine-tuning, deliver measurable ROI in the most cost-effective way. Beyond crafting prompts, you will design and build robust, scalable products: benchmarking candidate Foundation Models across the model stack (from GPT-x, Claude, and Gemini to edge models like Mistral), rapidly iterating prototypes, and validating ideas directly with users using frameworks such as LangChain, LlamaIndex, and pgvector. 
We work closely with leading technology partners including Anthropic (Claude), OpenAI, Databricks, and AWS. In practice that means early access to new model releases, direct engineering channels to the labs, funded certifications, and the freedom to pick the right tool, not just the one you’re locked into. 
What you’ll actually do 

• Sit with a client’s team, work out where AI actually earns its keep (and where it doesn’t), and set the direction for turning that into something that ships.
• Lead the design and delivery of LLM-based systems: autonomous agents, RAG pipelines, workflow automation, and conversational interfaces, and make the architecture calls that go with them.
• Own the integration of these solutions into clients’ environments (APIs, databases, business tools), making sure they comply with applicable regulations (GDPR, EU AI Act, model licenses, etc.) and that risks are managed.
• Drive adoption across client organizations: shape the training approach, win over sceptics at every level, and iterate until solutions are embedded in daily work.
• Partner with executive stakeholders to refine solutions in production, track their business impact, and decide where to invest next.
• Be the person in the room who can talk to the engineers and to the board, and be believed by both.
• Coach and develop the team around you, and set the quality bar for how the practice builds and delivers AI.

You’ll thrive here if:

• You have a strong grounding in computer science, AI, or a related technical field, and you have a track record of building systems that reached production.
• You have 5+ years of professional experience, including experience leading teams or engagements. We hire for leadership and judgment as much as technical depth.
• You have deep hands-on experience with LLMs, in production, in research, or in substantial projects: advanced prompting, RAG, fine-tuning, agent orchestration, and systematic evaluation of model outputs (evaluation sets, regression testing, and quality frameworks).
• You write Python you’d be proud to put in front of any engineering team, and you can quickly pick up whatever language a client’s stack demands.
• You’re experienced at integrating APIs and connecting heterogeneous systems, and you can make sound architecture decisions for them.
• You have a strong sense of client context. You know how to decide what’s worth building, set priorities, and deliver measurable value at pace.
• You can lead non-technical teams through transformation, with the teaching ability, active listening, and communication skills to bridge very different areas of expertise.
• You want to take ownership of high-value engagements and help shape the direction of a dynamic, fast-growing AI practice, including developing the people in it.
• You’re fluent in English, French and Dutch. German is a strong advantage, and we support you in learning it if you are not there yet.
  Bonus points for:
• Experience leading teams building with applied AI frameworks (LangChain, LlamaIndex, OpenAI SDK, Anthropic SDK, etc.).
• Experience overseeing the deployment and operation of solutions in a cloud environment (AWS, Azure, or GCP).
• Experience setting standards for MLOps/LLMOps practices (CI/CD for models, prompt versioning, evaluation pipelines, observability).
• Deep understanding of vector databases and related concepts (e.g., embeddings, neural networks, latent space).

Why join Sia

• You ship at scale. You’ll own engagements measured in weeks to quarters, with your solutions going live in front of real users and across the client’s organization, and you’ll set how your teams make that happen.
• Range with depth. You’ll work across several industries and architectures a year, building the judgement to know what works and to pass it on to others.
• A practice you help shape. The AI practice is growing fast, and you’ll have a real say in how it delivers, how it hires, and how it builds its methods.
• Direct access to decision-makers. You’ll sit with business leaders and boards from the start, and you’ll be the one who represents the practice in those rooms.
  What we offer
• A competitive salary and strong benefits, including a mobility budget or company car, hospital insurance, and a performance-related bonus.
• A dedicated learning budget, funded partner certifications (Anthropic, AWS, Databricks), and paid conference time, plus the chance to shape learning for your team.
• Hybrid working from our Brussels or Antwerp office, with real flexibility over where the deep work happens.
• A clear path into practice leadership, with the chance to lead teams, mentor others, and grow into senior client-facing roles.
   
  We are unable to provide a work permit for this position.
  Sia is an equal opportunity employer. All aspects of employment, including hiring, promotion, remuneration, or discipline, are based solely on performance, competence, conduct, or business needs. 

Sia is an equal opportunity employer. All aspects of employment, including hiring, promotion, remuneration, or discipline, are based solely on performance, competence, conduct, or business needs. 

Most GenAI never leaves the demo. We hire for the people who get it into production, and into daily use. The Forward Deployed Engineer closes that gap: a field engineer who builds GenAI applications (agents, RAG pipelines, copilots) and makes sure they get adopted, embedded in daily workflows, and deliver measurable value. You quickly grasp a client’s operational challenges, design a tailored response, deploy it, and bring teams along in the transformation. 
You will operate at the intersection of Data Science, ML/Platform Engineering, and client delivery, helping customers find the right level of sophistication, semantic search, RAG, agents, or fine-tuning, deliver measurable ROI in the most cost-effective way. Beyond crafting prompts, you will design and build robust, scalable products: benchmarking candidate Foundation Models across the model stack (from GPT-x, Claude, and Gemini to edge models like Mistral), rapidly iterating prototypes, and validating ideas directly with users using frameworks such as LangChain, LlamaIndex, and pgvector. 
We work closely with leading technology partners including Anthropic (Claude), OpenAI, Databricks, and AWS. In practice that means early access to new model releases, direct engineering channels to the labs, funded certifications, and the freedom to pick the right tool, not just the one you’re locked into. 
What you’ll actually do 

• Sit with a client’s team, work out where AI actually earns its keep (and where it doesn’t), and set the direction for turning that into something that ships.
• Lead the design and delivery of LLM-based systems: autonomous agents, RAG pipelines, workflow automation, and conversational interfaces, and make the architecture calls that go with them.
• Own the integration of these solutions into clients’ environments (APIs, databases, business tools), making sure they comply with applicable regulations (GDPR, EU AI Act, model licenses, etc.) and that risks are managed.
• Drive adoption across client organizations: shape the training approach, win over sceptics at every level, and iterate until solutions are embedded in daily work.
• Partner with executive stakeholders to refine solutions in production, track their business impact, and decide where to invest next.
• Be the person in the room who can talk to the engineers and to the board, and be believed by both.
• Coach and develop the team around you, and set the quality bar for how the practice builds and delivers AI.

You’ll thrive here if:

• You have a strong grounding in computer science, AI, or a related technical field, and you have a track record of building systems that reached production.
• You have 5+ years of professional experience, including experience leading teams or engagements. We hire for leadership and judgment as much as technical depth.
• You have deep hands-on experience with LLMs, in production, in research, or in substantial projects: advanced prompting, RAG, fine-tuning, agent orchestration, and systematic evaluation of model outputs (evaluation sets, regression testing, and quality frameworks).
• You write Python you’d be proud to put in front of any engineering team, and you can quickly pick up whatever language a client’s stack demands.
• You’re experienced at integrating APIs and connecting heterogeneous systems, and you can make sound architecture decisions for them.
• You have a strong sense of client context. You know how to decide what’s worth building, set priorities, and deliver measurable value at pace.
• You can lead non-technical teams through transformation, with the teaching ability, active listening, and communication skills to bridge very different areas of expertise.
• You want to take ownership of high-value engagements and help shape the direction of a dynamic, fast-growing AI practice, including developing the people in it.
• You’re fluent in English, French and Dutch. German is a strong advantage, and we support you in learning it if you are not there yet.
  Bonus points for:
• Experience leading teams building with applied AI frameworks (LangChain, LlamaIndex, OpenAI SDK, Anthropic SDK, etc.).
• Experience overseeing the deployment and operation of solutions in a cloud environment (AWS, Azure, or GCP).
• Experience setting standards for MLOps/LLMOps practices (CI/CD for models, prompt versioning, evaluation pipelines, observability).
• Deep understanding of vector databases and related concepts (e.g., embeddings, neural networks, latent space).

Why join Sia

• You ship at scale. You’ll own engagements measured in weeks to quarters, with your solutions going live in front of real users and across the client’s organization, and you’ll set how your teams make that happen.
• Range with depth. You’ll work across several industries and architectures a year, building the judgement to know what works and to pass it on to others.
• A practice you help shape. The AI practice is growing fast, and you’ll have a real say in how it delivers, how it hires, and how it builds its methods.
• Direct access to decision-makers. You’ll sit with business leaders and boards from the start, and you’ll be the one who represents the practice in those rooms.
  What we offer
• A competitive salary and strong benefits, including a mobility budget or company car, hospital insurance, and a performance-related bonus.
• A dedicated learning budget, funded partner certifications (Anthropic, AWS, Databricks), and paid conference time, plus the chance to shape learning for your team.
• Hybrid working from our Brussels or Antwerp office, with real flexibility over where the deep work happens.
• A clear path into practice leadership, with the chance to lead teams, mentor others, and grow into senior client-facing roles.
   
  We are unable to provide a work permit for this position.
  Sia is an equal opportunity employer. All aspects of employment, including hiring, promotion, remuneration, or discipline, are based solely on performance, competence, conduct, or business needs. 

Sia is an equal opportunity employer. All aspects of employment, including hiring, promotion, remuneration, or discipline, are based solely on performance, competence, conduct, or business needs.