WE’RE HIRING! If you love data and are looking for unlimited growth opportunities, we want to talk with you about joining Further. Further is a data, cloud, and AI company whose focus is helping companies turn raw data into the right decisions.

We have an award winning culture of extraordinary people. Our purpose is to enable people to thrive so that businesses can thrive. We believe that the work you do should matter - it should be meaningful to you professionally and personally, and it should have a positive impact on both you and our clients.

If this sounds exciting to you, let’s chat! SENIOR AI ENGINEER We are hiring a Senior AI Engineer to lead the development of our cloud-based (Google Cloud), commercial AI products. You will bridge the gap between experimental data science prototypes and production-grade software.

You will architect the robust systems and LLMOps workflows necessary to transform AI models into reliable, enterprise-ready applications. By designing stable backend architectures and seamless integration layers, you will ensure our AI solutions are not just functional, but ethical, efficient, and high-value products that meet the rigorous demands of our commercial clients. What experience should you have: 10+ years of years experience developing and deploying Data Science and ML solutions 3 years of experience working directly with GenAI/RAG/LLM architecture Expert proficiency in Python AI application development and modern API architecture (REST, GraphQL, gRPC) using enterprise standards like static type checking and data validation.

Deep experience building production applications with LLM frameworks such as LangChain, LangGraph or LlamaIndex. Hands-on expertise with vector databases (Pinecone, Weaviate, PostgreSQL) and search algorithms. Strong understanding of LLMOps principles, including model registry, versioning, and serving infrastructure specifically in Google Cloud.

Nice To Have

: Experience in Typescript development for prototyping and integrations

: Proficiency with git workflows and understanding of standard application development processes

Preferred Qualifications

Knowledge of advanced prompt engineering and fine-tuning techniques (LoRA, PEFT). Experience optimizing inference costs and latency for large-scale deployments. Previous experience in a client-facing consulting role, managing diverse stakeholders and navigating complex organizational structures.

Any Google Cloud Professional Certification What you’ll be doing in this role: Lead the implementation of rigorous evaluation frameworks to monitor model performance, drift, and cost in real-time. Architect and develop high-performance backend services and APIs using Python (FastAPI) to serve large language models at scale. Design advanced Retrieval-Augmented Generation (RAG) systems, selecting and managing vector databases and optimizing embedding strategies for accuracy and speed.

Establish comprehensive model observability and guardrail systems to monitor real-time performance, detect distribution drift, and implement automated safety filters that mitigate hallucinations, bias, and toxic outputs in production environments. Build robust integration layers that connect AI agents securely to external enterprise systems, CRMs, and legacy databases. Conduct code reviews, provide technical guidance, and foster a culture of continuous learning and innovation within the engineering team.

Collaborate with infrastructure teams to define deployment strategies, ensuring solutions scale dynamically under load. Define the end-to-end architecture for AI products on cloud platforms (preferably Google Cloud Platform), ensuring high availability, security, and cost-effectiveness. What you’ll need to accomplish in your first year: Develop reusable internal libraries and architectural patterns and standards to accelerate the delivery of AI solutions across multiple client engagements.