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Forward Deployed AI Engineer

Role overview

Qualifications

  • Experience in building production AI systems
  • Ability to work embedded in client environments
  • Strong data engineering skills
  • Familiarity with multi-agent systems and orchestration

Responsibilities

  • Design and build production agentic AI systems
  • Conduct data engineering tasks including data ingestion and classification
  • Own evaluation and accuracy of AI models
  • Ensure knowledge transfer and system handover to clients

About the company

gravity9 logo

gravity9

IT Services & IT Consulting

Realising the next phase of your digital journey requires more than just great technology. At gravity9, we have a different approach. With deep experience and personality, our team of designers and engineers unite art and science, to realise the next chapter in your digital journey.

Company details

Company typeScaleup
IndustryIT Services & IT Consulting
Company size51 - 200

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Job description

gravity9 is a boutique IT consulting company headquartered in the UK with offices in the US, Canada, Poland, and Colombia. Our team has deep experience in engineering, experience design and product management. We enjoy a challenge and pride ourselves on working with our clients on their most complex problems, finding elegant and flexible solutions that help them transform their businesses.

Join Our Growing Team - Future Opportunities Await!

We are excited to share that our company is experiencing significant growth and expansion, and as a result, we're on the lookout for talented individuals to join our team.

We want to be upfront about our hiring process. At this moment, we are in the process of securing projects that align with our business goals and objectives. Our intention is to ensure that once we bring new team members on board, they will have a meaningful and impactful role to play from day one. While we might not be able to extend an offer immediately, we are highly interested in considering you for these future projects.

If you're open to the idea of potentially joining our team in the future, we encourage you to continue with our interview process. We value your time and effort and believe that getting to know you better will help us make an informed decision.

Once you have effectively concluded the entire recruitment procedure, we will retain your profile and reach out to you once a suitable opportunity emerges. Additional interviews will not be necessary at this stage, and we anticipate being able to extend an offer to you promptly.

What does the recruitment process look like?

1. Recruiter Screen

In the first call, our recruiter will learn more about you and your story to check a potential fit for gravity9. This is also an opportunity to ask your questions about the role and company. This step might take around 60 mins.

2. Tech 1 Interview with our AI Practice Lead

In this meeting your potential future teammate will take a deeper dive into your experience and what you could bring to the team.
This step will take around 75 mins.

3. Tech 2 Interview with our software consultants

In this meeting your potential future teammate will take a deeper dive into your experience and what you could bring to the team.
This step will take around 60 mins.

4. Final Interview

You made it to the very last stage! Here we already strive to cooperate with you and give you an opportunity to meet our leadership team during this informal talk. This step will take around 30 mins.

The salary details for the role will be communicated ahead of the first recruitment meeting.

Thank you for considering the opportunity to be a part of our growing journey. We look forward to the possibility of working together and achieving great things.

Role Description

gravity9 is expanding its Forward Deployed Engineering team to build production agentic AI systems for enterprise clients, in partnership with leading frontier-model providers. We already support clients from different verticals to have agentic and RAG systems live in production across healthcare, financial services, retail and global logistics.

As a Forward Deployed AI Engineer you work embedded in the client's environment, from discovery, through architecture and build, to production and handover. This is end-to-end agent engineering, not proofs of concept and not advisory work. Two flavours of engagement:

  • Internal enterprise use cases, such as reconciliation and KYC workflows in financial services, clinical and claims workflows in healthcare, operations and supply-chain workflows in logistics.

  • Product- and customer-facing agents, more greenfield, often exploratory, built into the client's own product.

Engagements are typically a team of engineers over a few months, working shoulder-to-shoulder with the client's team including architects, DevOps and QA.

  • Embed with the client. Work hand-in-hand inside the client's environment, codebase and cloud tenancy, often in a hybrid team alongside their engineers. You are visible to the client from day one.

  • Design and build production agentic AI systems. Multi-agent orchestration, tool and function calling, retrieval, planning and routing, human-in-the-loop checkpoints, state and checkpointing, guardrails, failure handling and recovery.

  • Do the unglamorous data work. A large share of every engagement is data engineering: ingestion, flattening deeply nested structures, extracting content from unstructured documents, classification, summarisation, tagging, enrichment, indexing. Models reason over data, bad data beats a good model every time.

  • Own evaluation and accuracy. Establish a baseline eval dataset at the start of the engagement, automate grading, and track groundedness, faithfulness and retrieval quality per tool, not just at the agent level. Be ready to defend accuracy numbers to a sceptical enterprise stakeholder.

  • Engineer for cost and latency. Model selection and routing (cheaper, faster models for non-reasoning steps; frontier models where reasoning genuinely earns it), prompt and context budgeting, caching. Cost is a non-negotiable metric on every engagement.

  • Ship it properly. Observability and tracing, CI/CD, IaC, monitoring the client can actually operate, security and compliance review.

  • Transfer knowledge deliberately. We don't run a long-term support business. Every engagement is designed so the client owns and can extend the system after we leave. You architect with their team in the room, pair with their engineers, and hand over working monitoring and documentation.

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MR

Marcus Rivera

Chief Revenue Officer

m.rivera@company.com
linkedin.com/in/marcusrivera
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