SeniorFull TimeEN
Zenitech is a leading technology solutions provider dedicated to reshaping the global digital landscape. Headquartered in the UK, Zenitech operates internationally, with offices in Lithuania, Romania, and Hungary.
We use a bespoke approach depending on where the client is on their digital journey, comprising a combination of access to dedicated R&D labs, technology implementation advice, and specialist near-shore development talent. As an international community of individuals who are open to learning from each other, we collectively define and contribute to the digital future of our clients’ businesses.
Our client is a leading cloud-based business and financial planning software company, providing subscription-based solutions that help organizations make data-driven decisions. Recognized by Gartner in the Financial Planning Software market, they enable enterprise planning across finance, operations, sales, and supply chain through a highly scalable and extensible platform.
We're seeking a versatile GenAI Engineer who can work across the full stack of GenAI applications, model integration and prompt engineering. You'll build production-ready AI features that empower business users to leverage the power of GenAI within their planning workflows, requiring both deep ML knowledge and strong software engineering skills.
You’ll have the opportunity to join a greenfield team building transformative AI capabilities from the ground up
Work with cutting-edge conversational and agentic AI technologies to develop user-facing features that directly influence how businesses plan and make decisions
Experiment with the latest generative AI models and techniques while collaborating closely with talented engineers, data scientists, and product designers
Tackle unique challenges at the intersection of AI and enterprise software, while continuing to grow your skills across both machine learning engineering and full-stack development
Develop end-to-end GenAI features including backend API services, model integration, model monitoring, evaluations and deployments
Integrate and optimize LLMs for specific use cases in business planning, including prompt engineering, RAG implementation
Build conversational interfaces and agentic workflows that make complex planning tasks accessible through natural language
Implement evaluation frameworks to measure and improve GenAI feature quality, including accuracy, latency, and user satisfaction metrics
Design and develop APIs that expose AI capabilities to our client's platform and third-party integrations
Optimize model inference pipelines for performance, cost, and scalability in production environments
Implement monitoring, logging, and observability for GenAI systems to track usage, errors, and model behaviour
Collaborate with data scientists to productionize ML models and forecasting algorithms
Write comprehensive tests including unit tests, integration tests, and prompt regression suites
Participate in code reviews, technical design discussions, and knowledge-sharing sessions
Stay current with GenAI research and tools, evaluating new models and techniques for potential adoption
Contribute to an environment where different perspectives are valued, and where open collaboration leads to better technical decisions.
5+ years of software engineering experience with 2+ years focused on ML/AI systems
Strong programming skills in Python including experience with ML frameworks (PyTorch, TensorFlow, Transformers)
Experience building and deploying LLM-powered applications in production
Understanding of RESTful API design, microservices architecture, and cloud infrastructure
Experience with prompt engineering, RAG systems
Strong foundation in ML fundamentals including NLP, time-series analysis, or recommender systems
Familiarity with containerization (Docker), orchestration (Kubernetes), and CI/CD pipelines
Excellent problem-solving skills and attention to detail
Bachelor’s degree in computer science, Machine Learning, or related field
Nice to have:
Experience with GenAI frameworks (LangChain, LlamaIndex, Haystack, or similar)
Knowledge of vector databases (Pinecone, Weaviate, Qdrant) and embedding models
Experience with model serving frameworks (vLLM, TensorRT, Ray)
Background in forecasting, planning, or analytics applications
Familiarity with enterprise planning platforms
Experience with A/B testing and experimentation frameworks for AI features
Contributions to open-source ML projects or research publications
Experience with model observability tools (LangSmith, W&B, MLflow)
Remote/hybrid working model and flexible working hours
Referral programme
A culture of continuous growth, supported by our People Lead system and various training resources for your personal development
Agile mindset, simplified processes, and a great atmosphere where commitment and autonomy are celebrated
A community-first mindset, working with talented people across technology, products, and consulting
A fair, inclusive environment where diverse perspectives are valued, and people are trusted to do their best work
Charity events and programs
Impactful projects: Drive meaningful change through digital transformation projects and have an opportunity to make an impact on many industries.
Collaborative culture: Be part of a diverse, inclusive team committed to growth, innovation, and continuous learning.
Professional growth: Zenitech supports continuous learning and development through the People Lead system, helping you advance your skills and career.
Fair and transparent hiring: Our process is designed to be consistent, structured, and focused on your unique skills, potential, and the impact you’ll bring to the team.
Inclusive collaboration: We work across teams, disciplines, and locations, believing that the best outcomes are driven by diverse perspectives and a culture of shared ownership.
Zenitech celebrates diversity in all its forms and is committed to creating an inclusive environment where everyone feels valued for their unique contributions and perspectives. Inclusion at Zenitech is not separate from how we work — it’s part of our day-to-day culture. We build teams where people can contribute, be heard, and grow, because different perspectives lead to better thinking, stronger collaboration, and better outcomes for our clients.
If you require any adjustments during the application process, please let us know — we’re here to help.
You can learn more about our approach in our Diversity, Equity, Inclusion and Belonging Statement.
