Lead AI Engineer
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Key skills for this role
About the Role
Worley is seeking a Lead AI Engineer to design, prototype, and scale AI-powered solutions that enhance engineering workflows and automate knowledge-driven processes. The role requires 4+ years delivering AI/ML or GenAI solutions in production, with expertise in RAG, agentic workflows, and Python.
Key Skills for This Role
Responsibilities
- Design and implement AI solutions leveraging RAG, agentic workflows, and structured outputs.
- Define reusable architecture patterns tailored to engineering use cases.
- Recommend model strategies aligned to cost, performance, and security constraints.
- Ensure solutions remain model agnostic and adaptable to evolving enterprise platforms.
- Partner with Enterprise Architecture to align with standards, integration patterns, and security requirements.
- Lead a rapid MVP based delivery approach: develop solutions in short cycles, validate with users, iterate based on feedback.
- Transition validated solutions from Incubator environments to scalable enterprise architectures.
- Optimize solutions across performance, latency, cost, and reliability.
- Support structured handoff to production teams with clear architecture documentation and scaling guidance.
- Apply AI to complex engineering datasets to improve decision making and automation.
- Build and deploy RAG based applications to generate, validate, and augment engineering outputs.
- Partner with engineering and business teams to identify and prioritize high value AI opportunities.
Requirements
- Bachelor’s degree in Engineering, Data Science, Computer Science, or related discipline
- 4+ years of experience delivering AI/ML or GenAI solutions in production or near production environments
- Proven experience designing and implementing RAG architectures
- Proven experience designing and implementing agentic workflows and AI copilots
- Strong proficiency in Python and modern AI frameworks (e.g., PyTorch, LangChain or equivalent)
- Experience with cloud platforms and MLOps practices (CI/CD, Docker, MLflow or equivalent)
- Solid understanding of system architecture patterns (APIs, microservices, event driven systems)
- Proven ability to translate complex engineering or business problems into scalable AI solutions with measurable impact
- Strong communication skills with ability to work across technical and business teams
Full Job Posting
Role Summary
- Our Lead AI Engineer role plays a key role in enabling Worley’s digital transformation by designing, prototyping, and scaling AI powered solutions that enhance engineering workflows, automate knowledge driven processes, and unlock measurable business value across the project delivery lifecycle.
- This role bridges deep engineering domain expertise and advanced AI/ML capabilities, translating complex engineering data into intelligent, production ready systems.
Key Responsibilities
- AI Solution Design & Architecture: Design and implement AI solutions leveraging RAG, agentic workflows, structured outputs.
- Define reusable architecture patterns tailored to engineering use cases.
- Recommend model strategies aligned to cost, performance, and security constraints.
- Ensure solutions remain model agnostic and adaptable to evolving enterprise platforms.
- Partner with Enterprise Architecture to align with standards, integration patterns, and security requirements.
- Rapid MVP Development → Scaling → Delivery: Lead a rapid MVP based delivery approach.
- Develop solutions in short cycles (weeks, not months), validate with users, iterate based on feedback.
- Transition validated solutions from Incubator environments to scalable enterprise architectures.
- Optimize solutions across performance, latency, cost, and reliability.
- Support structured handoff to production teams with clear architecture documentation and scaling guidance.
- Engineering Workflow Transformation: Apply AI to complex engineering datasets to improve decision making and automation.
- Build and deploy RAG based applications to generate, validate, and augment engineering outputs.
Skills & Experience Required
- Bachelor’s degree in Engineering, Data Science, Computer Science, or related discipline.
- 4+ years of experience delivering AI/ML or GenAI solutions in production or near production environments.
- Proven experience designing and implementing RAG architectures.
- Proven experience designing and implementing agentic workflows and AI copilots.
- Strong proficiency in Python and modern AI frameworks (e.g., PyTorch, LangChain or equivalent).
- Experience with cloud platforms and MLOps practices (CI/CD, Docker, MLflow or equivalent).
- Solid understanding of system architecture patterns (APIs, microservices, event driven systems).
- Proven ability to translate complex engineering or business problems into scalable AI solutions with measurable impact.
- Strong communication skills with ability to work across technical and business teams.
Skills & Experience Preferred
- Masters degree in AI related discipline.
- Experience applying AI within engineering, energy, or industrial environments.
- Knowledge of engineering workflows and project delivery processes (e.g., PEPs, MDRs).
- Experience integrating AI into enterprise platforms (e.g., SharePoint, APIs, data platforms).
- Exposure to AI evaluation frameworks, LLMOps, or governance practices.
- Experience with computer vision or advanced analytics.
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