Overview
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 work closely with the Head of AI, Chief Architect, and the Product and Engineering teams to design and implement agentic capability into our cutting-edge compliance platform.
This is an opportunity to be part of a dynamic team developing new technologies to solve complex regulatory challenges.
Primary areas of expertise:
Implementing GenAI Solutions:
Apply GenAI solutions within our product with a strong focus on AI agent development.
Design and implement sophisticated LLM-based agent features, integrate them into our SaaS platform, and ensure reliability and security for regulatory compliance.
Collaborate with data scientists, engineers, and product teams to meet objectives and client needs, enabling autonomous or semi-autonomous execution of compliance tasks.
Collaborating on AI Strategy:
Align AI initiatives with the overall product roadmap and business goals.
Analyze impact using relevant metrics and KPIs, and refine AI strategy based on feedback to keep deployments dynamic and capable of innovation within 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 end-to-end architectural design of complex Generative AI systems, including retrieval and reasoning layers with vector databases, metadata filters, and graph-based memory to support regulatory intelligence and enhance AI agents.
AI Solutioning:
Combine expertise in LLM engineering with prompt optimization, model evaluation, RAG pipeline design (vector databases, graph retrieval), and robust agent orchestration with production-grade software engineering and MLOps/DevOps skills.
AI Frameworks:
Design and deploy complex agentic systems using frameworks such as LangChain, Autogen, LlamaIndex, LangGraph, CrewAI, Amazon Bedrock, Google ADK, etc., while abstracting tools effectively (tool schemas, action layers) for agent interaction with the compliance product.
System Integration:
Take GenAI applications from ideation through design, prototyping, production deployment, monitoring, and iteration within a SaaS product context.
Oversee integration of GenAI models into applications, ensuring seamless data flow and robust deployment strategies.
Scalability & Performance:
Architect GenAI solutions for high availability, scalability, and performance, considering compute, latency, and throughput.
Decide on orchestration strategies (e.g., ReAct vs. planner-executor) based on use case requirements for multi-agent regulatory workflows.
AI Performance and Evaluation:
Balance 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 in a multi-tenant SaaS environment.
Model Versioning for GenAI:
Maintain model documentation, lineage, and lifecycle tracking using model registries (e.g., MLflow, AWS SageMaker Model Registry).
Data Strategy:
Collaborate with data engineers/scientists to define data acquisition, preprocessing, and management to support GenAI training and inference.
Research & Innovation:
Stay abreast of Generative AI research and industry trends, evaluating applicability and trade-offs between NLP approaches and large-model heuristics to optimize agent efficiency.
Cross-Functional Collaboration:
Work with data scientists, ML engineers, software engineers, product managers, and stakeholders to translate requirements into designs.
Technical Leadership & Mentorship:
Provide technical leadership and mentorship to junior team members, fostering continuous learning and excellence.
Risk & Compliance:
Identify and mitigate risks (bias, fairness, privacy, security) and ensure regulatory compliance.
Nice to Have:
Knowledge of classic NLP techniques (NER, parsing, tf-idf) to complement LLM heuristics for regulatory text analysis.
Experience using ML models (re-rankers, regressions, embeddings) to improve agent decision-making in compliance use cases.
Graph theory and Graph Data Science for custom graph-based retrieval or memory stores to support richer agent reasoning.
Model Versioning and Registry (MLOps) skills for documentation, lineage, and lifecycle tracking (MLflow, AWS SageMaker).
Qualifications:
Education:
Bachelor's or Master's in Computer Science, AI, ML, or related field.
Ph.D. preferred.
Experience:
10+ years in software architecture; 3-5 years in ML/AI architecture; proven experience deploying large-scale Generative AI in production.
Technical Skills:
Python proficiency; experience with TensorFlow, PyTorch, Hugging Face; strong cloud platform experience (AWS, Azure, GCP); containerization (Docker, Kubernetes) and MLOps (MLflow, Kubeflow, SageMaker); familiarity with Spark/Dask is a plus; solid data structures and software design principles.
Problem-Solving:
Exceptional analytical and creative problem-solving abilities.
Communication:
Excellent verbal and written communication to articulate complex concepts to technical and non-technical audiences.
About us:
Compliance & Risks is a leading provider of market access and product compliance SaaS solutions, with a global footprint across technology, consumer goods, retail, industrial, and life sciences sectors.
Our C2P platform enables uninterrupted market access by monitoring and managing key product requirements, regulations, and standards.
We serve over 220+ global enterprise customers including GE, Google, Nike, Amazon, Ikea, Bose, Vaillant, Unisys, Samsung and Fujitsu.
We are an equal opportunities employer.
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