Job Title: AI Solutions Engineer
Location: Basingstoke, UK (Hybrid)
Job Type: Full-Time, Permanent
Department: AI Engineering
Reports To: Head of AI Engineering
About the Role
Techgroove is seeking a talented and ambitious AI Solutions Engineer to join our growing AI Engineering team. This is a pivotal role in our company's strategic shift towards becoming a full AI powerhouse. You will sit at the intersection of cutting-edge AI research and real-world business delivery — designing, building, and deploying intelligent solutions that create tangible, measurable value for our enterprise clients. You will work across the full solution lifecycle, from client discovery through architecture, deployment, and ongoing reliability, alongside data scientists, cloud architects, and business consultants in cross-functional squads.
Responsibilities
Solution Design & Delivery
- Design, develop, and deploy end-to-end AI solutions using large language models (LLMs), machine learning frameworks, and cloud AI services
- Architect and implement RAG (Retrieval-Augmented Generation) systems, AI agents, and conversational AI pipelines tailored to client requirements
- Develop proof-of-concept AI applications that demonstrate business value quickly and clearly
- Conduct technical discovery sessions with clients to understand requirements and translate them into AI architectural designs
AI & MLOps
- Build and optimise ML pipelines including data preprocessing, model training, evaluation, deployment, and monitoring
- Integrate AI models and APIs (OpenAI, Anthropic Claude, Azure OpenAI, Hugging Face) into client applications and workflows
- Optimise AI systems for performance, cost efficiency, and scalability in cloud environments
- Collaborate with data scientists and ML engineers to translate research prototypes into robust, production-ready systems
Safety & Responsible AI
- Implement AI safety, security, and responsible AI practices including bias testing, explainability tooling, and access controls
Collaboration & Documentation
- Participate in code reviews, architecture decisions, and technical mentoring of junior engineers
- Document AI architectures, model cards, and operational runbooks to ensure maintainability and knowledge transfer
- Stay at the forefront of AI research — evaluating and recommending new tools, frameworks, and approaches relevant to client needs
Qualifications
Required
- Bachelor's or Master's degree in Computer Science, AI, Mathematics, or a closely related field (or equivalent demonstrable experience)
- 2–5 years of hands-on software engineering or AI/ML engineering experience in production environments
- Strong Python proficiency — clean, testable, well-documented code by default
- Practical experience building with LLM APIs: OpenAI, Anthropic, Azure OpenAI, or comparable
- Experience with RAG architectures, vector databases (Pinecone, Weaviate, pgvector, Chroma), and embedding models
- Familiarity with ML frameworks: TensorFlow, PyTorch, scikit-learn, Hugging Face Transformers
- Experience with REST API development (FastAPI, Flask, Django REST) and microservices architectures
- Hands-on cloud experience on at least one of AWS, Azure, or GCP, particularly AI/ML service offerings
- Understanding of MLOps principles: model versioning, CI/CD for ML, experiment tracking, and model monitoring
- Strong communication skills — able to explain complex AI concepts to non-technical stakeholders clearly and confidently
Preferred
- Experience building agentic AI systems using LangChain, LlamaIndex, AutoGen, or similar orchestration frameworks
- Knowledge of fine-tuning LLMs (LoRA, QLoRA, PEFT) and prompt engineering best practices
- Experience with data streaming technologies: Kafka, Azure Event Hub, or AWS Kinesis
- Familiarity with AI evaluation frameworks and responsible AI practices (bias detection, fairness metrics, explainability)
- Experience in regulated industries: financial services, healthcare, or public sector
- MLOps tooling: MLflow, Kubeflow, Weights & Biases, or Azure ML pipelines
- Understanding of computer vision approaches: object detection, image classification, document digitisation
- AWS Certified Machine Learning – Specialty, AWS AI Practitioner, Microsoft Azure AI Engineer Associate, Google Professional Machine Learning Engineer, or DeepLearning.AI certifications (we sponsor certification study for the right candidates)
Tools & Technologies
- Languages/Frameworks: Python, FastAPI, LangChain, LlamaIndex
- AI/ML: OpenAI API, Anthropic Claude, TensorFlow, PyTorch, Hugging Face, MLflow
- Vector Databases: Pinecone, Weaviate
- Cloud: AWS, Azure, GCP
- Infrastructure: Docker, Kubernetes, Terraform, GitHub Actions
- Data: PostgreSQL, Redis
Benefits
- Competitive base salary, commensurate with experience, plus annual performance bonus
- £3,000 learning & development budget + full certification sponsorship
- Private healthcare and dental cover
- Hybrid working (Basingstoke HQ + remote)
- 25 days annual leave + bank holidays + birthday leave
- Company pension with employer contributions
Note: At this time, we are not seeking assistance from staffing or recruitment agencies.
Job Types: Full-time, Permanent
Pay: £55,000.00-£60,000.00 per year
Work Location: In person
