- Design, build, and deploy scalable production-ready solutions using Large Language Models (LLMs) for automation and advanced AI applications.
- Develop APIs and containerized web-based applications to integrate AI models into business workflows.
- Implement and manage LLMOps/MLOps pipelines for model deployment, monitoring, and lifecycle management.
- Set up automated workflows for model versioning, performance tracking, drift detection, and continuous evaluation against business KPIs.
- Integrate observability tools to enable real-time monitoring, system health checks, and compliance management.
- Develop and maintain data pipelines and CI/CD/CT workflows for model training, evaluation, and real-time inference.
- Analyze structured and unstructured data to generate insights and support strategic decision-making.
- Collaborate with software engineers, product managers, and business stakeholders to deliver end-to-end AI solutions.
- Communicate analytical findings and recommendations through reports, dashboards, and presentations.
- Work closely with UK-based teams to ensure smooth collaboration and alignment across time zones.
Required Skills & Abilities
- Strong programming expertise in Python with focus on clean, maintainable, and scalable code.
- Familiarity with web frameworks such as Flask, FastAPI, or Django.
- Proficiency in containerization and orchestration tools (e.g., Docker, Kubernetes).
- Experience with LLM fine-tuning, prompt engineering, and agent-based AI frameworks.
- Hands-on experience with modern GenAI frameworks such as LangGraph or LangChain.
- Strong expertise in data processing using Pandas, NumPy, and SQL.
- Experience working with large-scale data processing frameworks such as PySpark.
- Ability to translate complex business problems into scalable AI-driven solutions.
- Strong communication and collaboration skills, particularly when working with distributed teams.
- Ability to work in fast-paced environments while managing multiple projects simultaneously.
Qualifications & Experience
- Bachelor's or Master's Degree in Computer Science, Data Science, Statistics, or a related field.
- Minimum 3+ years of experience in software engineering, data science, machine learning, or AI engineering roles.
- Hands-on experience developing and deploying Generative AI / LLM applications in production environments.
- Experience implementing containerized deployments and CI/CD pipelines for AI applications.
- Exposure to cloud platforms such as Microsoft Azure and Databricks.
- Bonus: Experience working with large-scale datasets and distributed computing frameworks such as Apache Spark.
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