The Role
Design, build and deploy production-grade generative AI systems on AWS (Bedrock, SageMaker). Implement RAG, vector retrieval, agent orchestration, monitoring, governance, bias testing, and client-facing solution delivery with mentoring responsibilities.
Summary Generated by Built In
Cevo helps organisations build the capability for continuous evolution, turning transformation from a one-off program into a lasting ability to adapt, innovate and deliver better outcomes. As an Australian-owned, born in the cloud, AWS Premier Consulting Partner, we design and deliver modern cloud platforms, unlock data for insight and apply AI where it creates real value, while empowering teams so capability and impact extend well beyond each engagement. With onshore teams across Australia, we’ve partnered with more than 200 organisations across start-ups, commercial, enterprise and government.
Senior AI Engineer / Forward Deployed Engineer
Cevo is looking for a Forward Deployed Engineer (FDE) who sits at the intersection of consulting, cloud architecture, software engineering and AI delivery. This is not a traditional project role. You will embed directly with enterprise clients across financial services, energy and government to understand their business outcomes, build production-grade AI solutions and iterate rapidly until real value is delivered.
What You'll Do
1. Embed with Customers and Deliver Outcomes
Sit alongside clients to understand business problems, not just technical requirements. Define value and success metrics directly with product and executive teams. Build prototypes rapidly, learn from them and iterate, compressing the traditional discovery-design-build cycle into weeks. Present complex AI outputs in executive-ready language. Feed real-world product insights back into Cevo's internal platform and accelerator development.
2. Agentic & Generative AI Development
Design and build RAG pipelines using embedding models and vector databases. Use Anthropic to develop multi-agent systems with orchestration frameworks and create LLM-powered assistants integrated into enterprise workflows. Build prompt frameworks, tool-calling logic and structured response pipelines. Develop evaluation frameworks for hallucination risk and reasoning quality.
3. AWS-Native AI Engineering
Work hands-on with Amazon Bedrock: Models, guardrails and agents. Use Amazon SageMaker for training, fine-tuning, endpoints and pipelines. Build embedding pipelines and vector retrieval services. Implement monitoring and lifecycle management. Contribute to Cevo's reusable accelerators and internal tooling.
4. Integration and Full-Stack Deployment
Integrate AI systems into enterprise platforms including CRMs, ERPs, data lakes and internal tools. Deploy production solutions end-to-end not hand off to another team. Own the full journey from prototype to live system. Collaborate with cloud and security architecture teams throughout.
5. AI/MLOps, FinOps & Observability
Monitor model, prompt and embedding performance. Implement drift detection and audit trails. Build telemetry for LLM prompts and responses. Optimise for cost and latency. Maintain documentation, reproducibility and versioning.
6. Responsible & Governed AI
Embed explainability and transparency by design. Conduct bias and fairness testing. Design human-in-the-loop controls. Implement guardrails and content filtering. Align with APRA, ASIC and CPS 230/234 regulatory standards.
Required Experience
- 5–8+ years in software engineering, data science and ML
- 2+ years hands-on GenAI development: LLMs, RAG, agents, evaluation
- Demonstrated ability to deliver production-grade AI systems, end to end
- Strong Python and SQL
- Strong experience with Amazon Bedrock and Bedrock Agents
- Experience deploying ML models into production
- Understanding of APIs and AI services across the AWS ecosystem
- Strong communication and client-facing skills
Highly Desirable
- Experience in a Forward Deployed, embedded consulting or solutions engineering capacity
- SageMaker Pipelines
- Vector databases and Graph RAG
- Agent orchestration frameworks
- Regulated industry experience (financial services, energy, government)
- Model risk management experience
- Experience building AI platforms, assistants or internal tooling
Life at Cevo
Our people are at the heart of Cevo. We’re a passionate, curious team with deep consulting expertise, working together to help organisations across Australia continuously evolve. We value collaboration, knowledge-sharing and people are curious, take ownership and care deeply about the impact of their work for customers, colleagues and the wider community.
Benefits and ways of working
- $2,500 annual technology allowance to choose the tools and setup that work best for you.
- Strong learning and development culture, including $2,000 per year for professional courses and two paid days off to attend courses and exams.
- Support of the Cevo Hive Mind – a collaborative team that helps each other succeed.
- We reward and recognise achievements and contributions.
- An exciting start-up vibe, with enterprise-level projects and customers.
Additional information
- We are an equal opportunity employer and welcome all applications, particularly from underrepresented groups.
- At this stage, we can only consider candidates with unrestricted local working rights.
- We don’t require assistance from recruitment agencies.
Skills Required
- 5-8+ years' experience in Data Science, ML or as a Developer
- 2+ years GenAI Development (LLMs, RAG, agents, tuning, evaluation)
- Demonstrated ability to deliver production-grade AI systems
- Strong Python and SQL
- Strong experience with Bedrock Agents
- Experience deploying models into production
- Understanding of APIs and AI services
- Strong communication and client-facing skills
- Unrestricted local working rights
- SageMaker Pipelines
- Vector DBs
- Graph RAG
- Agent orchestration
- Regulated industry experience (APRA/ASIC/CPS standards)
- Model risk management experience
- Experience building AI platforms or assistants
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The Company
What We Do
Cevo is a technology consultancy that helps organizations build lasting capabilities in cloud, data, and AI. They focus on modernizing platforms, automating delivery, and empowering teams to innovate continuously. By embedding AI into their delivery processes, they help clients move from pilots to production-ready systems, ensuring that transformation becomes a habit rather than a one-off project.
