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SunCore Digital

AI Developer

Reposted 15 Days Ago
Hybrid
London, England, GBR
Mid level
Hybrid
London, England, GBR
Mid level
Design, build, deploy, and optimize production AI systems, including LLM integrations, RAG pipelines, embeddings, vector search, predictive models, and inference systems. Collaborate with product and engineering teams to translate business needs into scalable solutions for recommendations, risk scoring, forecasting, and workflow automation. Own data pipelines, monitoring, evaluation, security, privacy, documentation, and continuous model improvement across cloud environments.
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About the Role

SunCore Digital is seeking an experienced AI Developer to design, build, and deploy intelligent systems that power our next generation of client‑facing and internal automation tools. This role is ideal for someone who thrives at the intersection of software engineering, machine learning, and product strategy — someone who can translate complex business logic into scalable, production‑ready AI solutions.

You will work closely with engineering, product, and leadership to architect AI modules that support personalized recommendations, risk modeling, workflow automation, and data‑driven insights across our unified workspace platform.


Key Responsibilities

•        Design, build, and deploy AI‑powered features using Python, modern ML frameworks, and cloud‑native tooling.

•        Develop and integrate LLM‑based systems (OpenAI, Azure OpenAI, Hugging Face, etc.) into production applications.

•        Architect data pipelines, embeddings, vector search, and retrieval‑augmented generation (RAG) workflows.

•        Collaborate with product and engineering to translate business requirements into technical AI solutions.

•        Build models and inference systems that support personalization, risk scoring, forecasting, and decision support.

•        Optimize model performance, latency, and cost across cloud environments.

•        Implement monitoring, evaluation, and continuous improvement processes for deployed models.

•        Ensure security, privacy, and compliance in all AI‑related data handling.

•        Contribute to architectural decisions, documentation, and best practices for AI development.

•        Stay current with emerging AI technologies and propose new capabilities that strengthen our platform.

·         Work with structured and unstructured data, ensuring data quality, versioning, and evaluation readiness.


Required Skills & Experience

·         4+ years of experience in AI/ML engineering or applied machine learning.

·         Strong proficiency in Python, including frameworks such as TensorFlow, PyTorch, Scikit‑learn, or similar.

·         Experience integrating LLMs, embeddings, and vector databases (Pinecone, Weaviate, Redis, etc.).

·         Hands‑on experience with RAG pipelines, prompt engineering, and model fine‑tuning.

·         Solid understanding of data structures, algorithms, and API development.

·         Experience deploying AI systems in cloud environments (Azure, AWS, or GCP).

·         Familiarity with DevOps practices: Docker, CI/CD, monitoring, and observability.

·         Strong problem‑solving skills and ability to work in a fast‑paced, remote‑first environment.

·         Excellent communication skills and ability to explain complex concepts to non‑technical stakeholders.

·         Experience designing end-to-end AI systems, from data ingestion to inference and monitoring.

·         Experience with model evaluation, testing, and defining quality metrics for AI systems.




Preferred Qualifications

• Experience with financial modeling, risk scoring, or recommendation systems.

• Background in NLP, time‑series forecasting, or reinforcement learning.

• Experience building AI‑powered user experiences in web or mobile applications.

• Knowledge of data governance, privacy, and compliance frameworks.

• Prior experience in a startup or high‑growth environment.


What We Offer

• Competitive compensation and performance‑based bonuses

• Profit‑share participation

• Remote‑first culture with flexible working hours

• Opportunity to shape a first‑to‑market AI platform

• Collaborative, high‑ownership environment

• Professional development support and growth opportunities

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