GenAI Architect

Job Title: GenAI Architect

Reports to: Head of AI

Location: Ireland / UK - Remote, may consider applicants from elsewhere in Europe

Purpose: 

The GenAI Architect is a critical role responsible for designing, developing, and implementing scalable and robust Generative AI solutions that will drive our next generation of products and services. You will be instrumental in shaping our GenAI strategy, bringing state-of-the-art models from research to production, and fostering a culture of innovation.

Our challenge

We’re building the future of product and corporate compliance driven by AI, and have already delivered real value to our internal team and to our users with generative AI. As we look to 2025 and beyond, we believe the right combination of AI agents working on our users’ behalf can create dramatically more value as we transition our platform from traditional software-as-a-service to results-as-a-service.

The Role

We are seeking a GenAI Architect to play a critical role in designing and developing our agentic regulatory compliance solution.

You will play a leading role in designing and implementing agentic capability into our cutting-edge compliance platform, working closely with the Head of AI, Chief Architect, and the Product and Engineering teams. This is an opportunity to be part of a dynamic team developing new technologies to solve complex regulatory challenges. Your primary areas of expertise will include:

Implementing GenAI Solutions: The GenAI Architect will be responsible for the practical application of GenAI solutions within our product, with a strong focus on AI agent development. This includes designing and implementing sophisticated LLM-based agent features, integrating them seamlessly into our existing SaaS platform, and ensuring they function reliably and securely for regulatory compliance. You will collaborate closely with data scientists, engineers, and product teams to ensure these AI agent solutions meet our product's objectives and client needs, enabling autonomous or semi-autonomous execution of compliance tasks.

Collaborating on AI Strategy: This will involve working closely with the Head of AI, Chief Architect, and other stakeholders to align AI initiatives, especially those involving AI agents, with our overall product roadmap and business goals. You will analyze the impact of deployed GenAI solutions and AI agents through relevant metrics and KPIs, leveraging insights from these evaluations to refine and adjust our AI strategy for the product. By continuously integrating feedback and learnings from ongoing projects, the GenAI Architect will ensure that our AI strategy remains dynamic, responsive to evolving regulatory needs, and capable of seizing new opportunities for innovation and improvement within our compliance product through advanced agentic systems. This strategic collaboration guarantees that AI deployments not only address current challenges but also set the foundation for future advancements in regulatory technology.

Key Responsibilities:

• Strategic Vision & Roadmap: Define and evangelize the technical vision and roadmap for Generative AI within the organization, aligning with business objectives and identifying opportunities for GenAI adoption. 
• Architecture Design: Lead the end-to-end architectural design of complex Generative AI systems, including proficiency in architecting advanced retrieval and reasoning layers leveraging vector databases, metadata filters, and graph-based memory structures to support complex reasoning for regulatory intelligence and to enhance the capabilities of AI agents.
• AI Solutioning : Combined expertise in LLM engineering with prompt optimization and model evaluation, advanced RAG pipeline design including vector databases, graph-based retrieval, and robust agentic orchestration with production-grade software engineering and MLOps/DevOps skills.
• AI Frameworks : Ability to design and deploy complex agentic systems using industry-standard frameworks such as LangChain, Autogen (Microsoft), LlamaIndex, LangGraph, CrewAI, Amazon Bedrock, Google ADK etc while abstracting tools effectively (tool schemas, action layers, etc.), allowing agents to interact with our compliance product's functionalities.
• System Integration: Demonstrated ability to take a GenAI application, with a strong emphasis on AI agents, from ideation through design, prototyping, production deployment, monitoring, and iteration within a SaaS product context. Design and oversee the integration of GenAI models into various applications, ensuring seamless data flow, API design, and robust deployment strategies.
• Scalability & Performance: Architect GenAI solutions for high availability, scalability, and optimal performance, considering computational resources, latency, and throughput. Understanding when to apply orchestration strategies (e.g., ReAct vs. planner-executor) depending on specific use case requirements within a regulatory compliance product, especially for multi-agent systems or complex compliance workflows.
• AI Performance and Evaluation : Experience balancing performance, scalability, and cost in LLMOps and agent deployment, including token budgeting, usage quotas, and observability tools (e.g., Langsmith, Opik, Arize) for tracing and optimization, particularly in a multi-tenant SaaS environment.
• Model Versioning for GenAI: Skills in maintaining systematic model documentation, lineage, and lifecycle tracking using model registries (e.g. MLflow, AWS SageMaker Model Registry) to streamline collaboration and compliance.
• Data Strategy: Collaborate with data engineers and scientists to define data acquisition, preprocessing, and management strategies to support GenAI model training and inference.
• Research & Innovation: Stay abreast of the latest advancements in Generative AI research and industry trends, evaluating their applicability and potential for our products. Ability to manage the trade-offs between classic NLP approaches and large-model heuristics when required by efficiency goals for regulatory data processing, optimizing agent efficiency.
• Cross-Functional Collaboration: Work closely with data scientists, machine learning engineers, software engineers, product managers, and business stakeholders to translate requirements into technical designs.
• Technical Leadership & Mentorship: Provide technical leadership, guidance, and mentorship to junior team members, fostering a culture of continuous learning and excellence.
• Risk & Compliance: Identify and mitigate risks associated with GenAI deployment, including bias, fairness, privacy, and security, ensuring compliance with relevant regulations.

Nice to Have:

• Knowledge of Classic NLP techniques (NER, parsing, tf-idf, etc.) to complement LLM heuristics when lighter, cheaper, faster, or better would be a great addition to your skillset for regulatory text analysis, enhancing agent perception.
• Ability to use ML models (re-rankers, regressions, embeddings, etc.) that boost overall LLM application quality for compliance use cases, improving agent decision-making and accuracy.
• Graph theory and Graph Data Science: Custom graph-based retrieval or memory stores for agents; supports richer reasoning paths for complex regulatory relationships, enabling more sophisticated agent intelligence.
• Model Versioning and Registry (MLOps) - Skills in maintaining systematic model documentation, lineage, and lifecycle tracking using model registries (e.g. MLflow, AWS SageMaker Model Registry) to streamline collaboration and compliance.

Qualifications:

• Education: Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, or a related quantitative field. Ph.D. preferred.
• Experience:
  • 10+ years of experience in software architecture, with at least 3-5 years specifically focused on Machine Learning/AI architecture.
  • Proven experience designing and deploying large-scale Generative AI solutions in a production environment.
• Technical Skills:
  • Proficiency in programming languages such as Python, with experience in relevant AI/ML frameworks (e.g., TensorFlow, PyTorch, Hugging Face Transformers).
  • Strong understanding of cloud platforms (AWS, Azure, GCP) and their AI/ML services.
  • Experience with containerization technologies (Docker, Kubernetes) and MLOps platforms (e.g., MLflow, Kubeflow, AWS Sagemaker) as mentioned above
  • Familiarity with distributed computing frameworks (e.g., Spark, Dask) is a plus.
  • Solid understanding of data structures, algorithms, and software design principles.
• Problem-Solving: Exceptional analytical and problem-solving skills with a creative approach to complex challenges.
• Communication: Excellent verbal and written communication skills, with the ability to articulate complex technical concepts to both technical and non-technical audiences.

About us:

Compliance & Risks is the leading provider of market access and product compliance SaaS solutions and is recognized as the leading end-to-end global product compliance solution provider across the technology, consumer goods and retail, industrial goods and life sciences sectors. The company’s market leading SaaS platform, C2P, enables uninterrupted market access for enterprises selling products globally by monitoring and managing key product requirements, regulations and standards in their chosen markets. The C2P platform provides the world’s most comprehensive database of legislative information, insights and actions, linked to product workflows, to help clients bring products to markets faster with lower risk and ensure ongoing compliance.

The company serves over 220+ global enterprise customers including: GE, Google, Nike, Amazon, Ikea, Bose, Vaillant, Unisys, Samsung and Fujitsu.

We take pride in what we build

We are a product company. We understand the impact our product has on the world and for our company. We watch it iterate, evolve, grow. We can easily connect the code we write to the problems we are solving for companies who are trying to build and sell their products in the global market. Whether it’s a hoodie, a car or a laptop, we can see our code helping to get that product to the high street. 

We take pride in how we build

Our self organizing teams make the decisions in how they architect, implement and deliver the code that they write. We support the decisions they bring, and trust our teams to present the options that make most sense for the company, the team and for the growth of the individuals. 

We are a diverse team in Compliance & Risks and we are committed to building and promoting an inclusive place to work for everyone. We strive to attract and retain a diverse range of people into our organization.  We aim to increase the diversity of our employee base by growing our diverse talent pipeline, including partnerships with organizations like Resilient Coders, Women who code, Women in Tech. We are committed to equality of opportunity for all employees, by promoting a work environment free from bullying, discrimination or harassment. Compliance & Risks is an equal opportunities employer.