At Netcall, we deliver powerful low-code, robotic process automation (RPA), and contact centre solutions that enable organisations to transform and streamline their processes. Central to our innovative platform, Liberty, is our dedicated Liberty AI Team, which integrates sophisticated, robust, and thoroughly tested AI capabilities across various products including low-code development, process mapping, automation, and customer service solutions. Our AI team collaborates closely with diverse product teams, ensuring seamless integration and maximising value through intelligent, user-focused enhancements.
Purpose of Role:
To maintain, enhance, and deploy AI services and codebases, ensuring high-quality integration and performance of machine learning models and generative AI solutions within the Netcall Liberty platform.
Key Responsibilities:
* Maintains and improves AI codebases for reliability and performance.
* Deploys and manages machine learning platforms for predictive model training.
* Implements and maintains generative AI systems with frameworks like SGLang, TGI, vLLM.
* Optimises natural language processing (NLP) tasks (summarisation, sentiment analysis, keyword extraction, categorisation).
* Develops and maintains retrieval-augmented generation (RAG) systems, indexing, embedding, and reranking.
* Builds evaluation frameworks assessing AI output faithfulness, relevance, and truthfulness.
* Enhances solutions with a focus on efficient compute usage for environmental sustainability, cost-effectiveness, and performance.
* Supports and contributes to improvements in AWS infrastructure, considering architecture optimisation, scalability, and robustness in collaboration with the DevOps team.
* Integrates AI solutions across backend infrastructure and front-end interfaces.
* Investigates and resolves complex technical issues with proactive debugging.
* Communicates effectively to stakeholders of varying technical expertise.
* Mentors junior team members, promoting best practices and skills development.
Essential Skills:
Cloud & Infrastructure:
* Foundational understanding of AWS or other cloud platforms, with an awareness of deploying and managing multi-tenant infrastructure.
* Ability to contribute ideas for architectural optimisation, improving scalability and robustness with support from the DevOps team.
Programming:
* Excellent programming and debugging skills in Python, including libraries like pandas, FastAPI, and Pydantic.
* Experience with version control systems, particularly Git.
* Ability to maintain and enhance APIs.
* Understanding of database management using PostgreSQL, including database models and entity diagrams.
ML/AI:
* Strong knowledge and practical experience in machine learning model training, evaluation, and deployment.
* Experience with AutoML libraries (e.g., AutoKeras).
* Solid experience with natural language processing (NLP) tasks and retrieval-augmented generation (RAG) systems.
* Expertise in embedding models, indexing techniques, and reranking methods.
* Familiarity with frameworks and libraries like HuggingFace and LangChain.
Deployment:
* Proficiency with deploying large language models (LLMs) using frameworks like SGLang, TGI, or vLLM.
* Proficiency in Linux and command-line interface for system administration and automation.
* Basic foundation in AWS or other cloud service providers to deploy multi-tenant infrastructures, managing and segregating user access control.
* Understanding of Kubernetes and containerised applications orchestration, including inter-service communication.
Development Methodologies:
* Familiarity with Agile development processes including daily stand-ups, weekly catch-ups, retrospectives, and hybrid approaches.
Desirable Skills:
* Familiarity with agentic AI frameworks such as PydanticAI or smolagents.
* Experience with fine-tuning large language models (LLMs).
* Interest or experience with MCP, A2A, or AutoGen.
* Keeps up to date with the latest trends in RAG solutions, agentic AI, and generative AI implementations.
Behavioural Competencies:
* Accountability: Takes ownership and responsibility for tasks and outcomes.
* Proactiveness: Anticipates needs, takes initiative, and seeks continuous improvement.
* Agility: Demonstrates flexibility and adaptability in a dynamic environment.
* Customer Focus: Prioritises user experience and customer satisfaction.
* Collaboration: Effectively works with and mentors colleagues, promoting teamwork and shared success.
* Communication: Clearly articulates complex technical information to diverse stakeholders.