AI Engineer​/AI Implementation Lead

We are seeking a highly capable AI Engineer / AI Implementation Lead to serve as a key execution partner to the Head of AI. This role is responsible for translating AI strategy into production-ready solutions across the organization—owning the design, implementation, and scaling of AI systems that drive measurable business impact.

You will work closely with product, engineering, data, risk, and business stakeholders to deliver AI-powered capabilities, with a strong emphasis on LLMs, applied ML, automation, and responsible AI deployment
. This is a hands-on role for someone who thrives in ambiguity and enjoys building practical, scalable AI systems.

• Design, build, and deploy AI-powered systems, including LLM-based applications, ML models, and intelligent automation workflows
• Lead end-to-end AI implementations from concept through production and iteration
• Translate business problems into technical AI solutions with clear success metrics

• Develop and optimize LLM-based solutions (e.g., RAG pipelines, agents, summarization, classification, decision support)
• Implement prompt engineering, retrieval strategies, evaluation frameworks, and guardrails
• Stay current on emerging AI tools, models, and architectures, and assess their applicability

• Collaborate with data and platform teams on model deployment, monitoring, and lifecycle management
• Ensure solutions meet performance, security, and compliance requirements

• Partner with product managers, engineers, analysts, and business leaders to identify high-impact AI use cases
• Communicate technical concepts clearly to non-technical stakeholders
• Support change management and adoption of AI-driven workflows

• Contribute to responsible AI practices, including model evaluation, bias mitigation, explainability, and auditability
• Help define standards, tooling, and best practices for AI development across the organization

• 5+ years of experience in software engineering, machine learning, or applied AI roles
• Hands-on experience building and deploying AI or ML systems in production
• Strong experience with Python and modern ML / AI libraries and frameworks
• Practical experience with LLMs (e.g., OpenAI, Anthropic, open-source models), including prompt design and system integration
• Solid understanding of data pipelines, APIs, and cloud-based architectures
• Ability to work independently, own projects, and operate effectively in a fast-paced environment

• Experience with RAG architectures, vector databases, embeddings, and search systems
• Familiarity with MLOps / LLMOps practices (monitoring, evaluation, versioning)
• Experience in regulated or data-sensitive environments (e.g., financial services)
• Exposure to agent-based systems or workflow orchestration
• Prior experience mentoring or leading technical initiatives

• AI projects move from idea to production faster and with higher quality
• Business teams adopt AI tools that meaningfully improve efficiency, decision-making, or customer experience
• The AI stack becomes more robust, reusable, and scalable over time

• Direct impact on the company’s AI strategy and execution
• Opportunity to shape how AI is responsibly deployed across the organization
• High visibility role with significant ownership and autonomy
• Work at the intersection of cutting-edge AI and real-world business problems