We are launching a strategic pool of AI specialists to accelerate the growth of our AI Practice and turn strong market demand into scalable, repeatable capabilities. This role goes beyond project delivery-it is about shaping how AI is built, shared, and scaled across the company.

As part of this group, you will play a key role in internal capability development, with a strong focus on designing and evolving AI Accelerators-reusable frameworks, templates, and reference architectures covering GenAI, LLM-based solutions, ML pipelines, and cloud-native AI systems. These accelerators will become the backbone of our AI offerings, enabling faster delivery, higher quality, and consistent technical standards across projects.

A second core dimension of the role is knowledge leadership. Strategic hires will actively contribute to internal knowledge-sharing initiatives: technical deep dives, hands-on workshops, demos, and best-practice sessions covering topics such as GenAI orchestration, RAG, model deployment, prompt and system design, observability, and cost-efficient AI architectures. You will help raise the overall AI maturity of the organization while mentoring engineers and influencing technical direction. In addition, members of this group will act as AI project jumpstarters, joining new client engagements for up to 50% allocation over 1-2 months. In this capacity, you will help define solution architectures, validate technical approaches, build initial prototypes, and set strong engineering foundations before teams scale. This gives you exposure to diverse domains and cutting-edge AI use cases while maximizing your impact across multiple initiatives.

Project Description

We are looking for a highly skilled and innovative Machine Learning Engineer to develop and expand our Generative AI and Computer Vision capabilities. This role involves accelerating Technical Sales Support, Architecture and PoC development.

Technologies

• Python
• Git, CI/CD practices for ML and data pipelines
• AWS and/or Azure
• PyTorch, TensorFlow
• MLflow
• LLMs and NLP tasks
• Generative AI concepts
• LangChain/LangGraph, LlamaIndex
• Qdrant, Pinecone, Weaviate, FAISS or similar
• RNNs, Transformers
• Dataset labeling, annotation tools (e.g., Label Studio, CVAT)
• Prometheus, Grafana, DataDog, OpenTelemetry
• YOLO, SDD
• Segmentation models
• Image Classification

What You'll Do

• Lead the design, development, and deployment of scalable ML services;
• Architect and implement AI/ML solutions, ensuring model quality, governance, and security;
• Optimize ML workflows for performance and cost efficiency on cloud platforms (AWS, Azure, or GCP);
• Collaborate with data scientists, analysts, and business stakeholders to understand ML requirements;
• Mentor and guide junior engineers, promoting best practices in ML engineering;
• Develop and maintain documentation, ML models, and technical standards;
• Monitor, troubleshoot, and resolve issues in production for ML pipelines and environments;
• Stay up-to-date with emerging trends and technologies in AI/ML field;

Job Requirements

• Bachelor’s or Master’s degree in Computer Science, Engineering, Mathematics, or a related field;
• 5+ years of experience in ML engineering, with at least 1 years of hands-on experience with LLMs;
• Strong proficiency in Python;
• Experience with cloud data platforms (AWS and/or Azure);
• Familiarity with CI/CD, DevOps, and infrastructure-as-code practices for ML engineering;
• Experience with data governance, security, and compliance in cloud environments;
• Excellent problem-solving, communication, and leadership skills;
• English: Upper Intermediate level or higher;

What Do We Offer

The global benefits package includes:

• Technical and non-technical training for professional and personal growth;
• Internal conferences and meetups to learn from industry experts;
• Support and mentorship from an experienced employee to help you professional grow and development;
• Health insurance;
• English courses;
• Sports activities to promote a healthy lifestyle;
• Flexible work options, including remote and hybrid opportunities;
• Referral program for bringing in new talent;
• Work anniversary program and additional vacation days.

About the Project
The platform uses AI agent architectures to generate and validate educational content at scale, serving multiple products across the organization. The team owns the end-to-end lifecycle: workflow design, LLM orchestration, evaluation, and production operations.

About the Role
We are looking for a senior AI engineer ready to work at the heart of production AI systems. You will  contribute directly to two core services: Conversation Brain, an LLM-driven conversation engine, and  Ambient ORA, a speech assessment engine powering multiple products. The role sits at the intersection of product engineering and AI science, bridging research outputs from the R&D team into production-grade services.

Key Responsibilities:

• Design, develop, and optimize AI-driven content generation workflows.
• Contribute directly to our codebases, building and maintaining agentic workflows using Python (FastAPI, CrewAI, LangGraph, LangChain) and Go where needed.
• Build and maintain agentic workflows using CrewAI, LangGraph, and LangChain.
• Ensure code quality through unit and integration tests written as part of the development workflow, in line with our shift-left approach where developers own test creation.
• Operationalize AI models in collaboration with the AI R&D.
• Implement LLM observability and evaluation using Langfuse, OpenLit, and New Relic.
• Design and run LLM evaluation benchmarks and regression detection.
• Integrate and manage resources across Azure (Container Apps, Service Bus, Blob Storage) and AWS.
• Ensure robust CI/CD pipelines and contribute to SDLC best practices.
• Package, deploy, and scale applications using Docker; Kubernetes experience is a plus.

Required Skills & Qualifications

• Strong Python development skills (FastAPI) and hands-on experience with agentic and LLM frameworks 
  (CrewAI, LangGraph, LangChain, or equivalent).
• Production experience with LLMs, including prompt engineering, model evaluation, and 
  operationalizing research outputs into production services (Azure OpenAI, Google Vertex AI).
• Practical experience with Azure services (Container Apps, Service Bus, Key Vault, Blob Storage) and 
  familiarity with AWS.
• Experience with LLM observability and monitoring tools (Langfuse, OpenLit, New Relic, or equivalent).
• Solid grasp of CI/CD, DevOps, and SDLC. Working knowledge of Docker, with k8s experience as a plus.
• Familiarity with ML/NLP tooling (PyTorch, Hugging Face Transformers, spaCy, scikit-learn) a strong plus.
• Daily user of AI development tools (Cursor, Claude Code, Copilot).
• Fluent English, spoken and written.
• Nice to have: Working knowledge of Go, with the ability to read, modify, and maintain existing Go 
  services

Benefits:

• Opportunities for certification and training
• Dual monitor setup and high-spec workstations
• English courses
• Gym allowance
• Medical Reimbursement
• Full salary covered up to 20 days of sickness
• Flexible working hours
• Loyalty scheme
• Team building activities, special events and conferences
• UK/EU Travel opportunities
• Snacks and drinks in the office