
Generative AI Solutions Engineer
2 weeks ago
Generative AI Solutions Engineer
Role Description
We are seeking a highly skilled Generative AI Solutions Engineer contractor to design, develop, and deploy cutting-edge AI solutions that leverage the latest advancements in large language models (LLMs), generative models (GANs, diffusion models), and autonomous agentic systems. This is a hands-on and technical role to turn AI into functional, scalable and real-world applications for corporations.
You will work closely with product managers, data scientists, and engineers to fine-tune models, design deterministic and more autonomous agent workflows, and integrate AI into applications that deliver measurable business impact. A strong foundation in Python and similar programming languages, mainstream AI agent frameworks, and AI integration technologies is essential, along with a keen ability to stay ahead of emerging trends in AI research and tooling.
There is a pathway for the contractor role to transition to a full-time position.
Responsibilities
AI Solution Design & Development
- Architect and implement generative AI solutions using models such as LLMs, GANs, and diffusion models.
- Fine-tune and optimise models for specific domain tasks and datasets.
- Design deterministic agentic workflows and autonomous agent systems with platforms such as LangGraph and LangChain.
Integration & Deployment
- Integrate generative AI pipelines with web, mobile, and enterprise applications.
- Implement Retrieval-Augmented Generation (RAG) workflows with vector databases (e.g., Pinecone, Weaviate, Milvus).
- Deploy, scale, and manage AI systems on AWS, Azure, or GCP.
MLOps & Quality Assurance
- Establish MLOps pipelines for continuous integration and deployment of models.
- Implement production-level monitoring, logging, and performance optimisation.
- Create systems for ongoing evaluation, safety testing, and bias mitigation.
Collaboration & Research
- Collaborate with cross-functional teams to translate business needs into AI-powered features.
- Track, evaluate, and apply the latest advancements in generative AI, prompting methods, and agent frameworks.
- Contribute to internal AI capability development and best-practice documentation.
Requirements
Technical Skills
- Proficiency in Python and experience with TensorFlow, PyTorch, or other deep learning frameworks.
- Proven expertise in generative AI technologies: LLMs, GANs, diffusion models, and fine-tuning strategies.
- Hands-on experience with LangChain or equivalent AI integration frameworks.
- Solid background in designing and deploying agentic workflows and autonomous agent systems.
- Experience with vector databases (e.g., Pinecone, Weaviate), RAG, and semantic search applications.
- Strong cloud deployment skills across AWS, Azure, or GCP.
- Familiarity with MLOps tooling and processes.
Professional Competencies
- Exceptional problem-solving and analytical thinking skills.
- Strong collaboration and communication abilities across technical and non-technical teams.
- Ability to work on both experimental prototypes and production-grade systems.
- Self-motivated, with a track record of delivering high-impact AI solutions.
- Commitment to staying current with evolving AI research and best practices.
Great-to-Have
- Knowledge of edge AI deployment and optimisation for low-latency environments.
- Experience with compliance and responsible AI governance frameworks.
- Exposure to multi-agent coordination, simulation-based testing, or hybrid symbolic-neural approaches
Sounds like an exciting opportunity to you? Please, send your application including your resume and link to your LinkedIn profile to
.
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