Technical Delivery Manager AI/ML

Job description summary

We are looking for a Technical Delivery Manager to lead our Digital Process Automation (DPA) initiatives. This role requires close collaboration with the Product Management, Policy Operations, and Content Operations teams to drive innovative automation solutions that enhance operational efficiency, increase revenue, and reduce manual effort. The ideal candidate will also ensure seamless integration of AI solutions into the business unit's (BU) product suite of applications.

This role requires leveraging spec-driven development (an AI-native development approach) and influencing business stakeholders to align with this approach.

Key responsibilities

• Lead and manage a team focused on developing automation solutions for manual-intensive workflows.
• Collaborate with the Product Management and Business Operations teams to identify automation opportunities.
• Oversee the design, development, and deployment of automation solutions with an AI-first strategy.
• Provide technical direction by leveraging a strong understanding of how AI technologies and generative AI can help solve business challenges, and guide the team in implementing AI-driven automation.
• Ensure strong collaboration with application development teams to seamlessly integrate automation solutions into the BU's product suite of applications, ensuring scalability and minimal disruption.
• Drive stakeholder management, ensuring effective communication and alignment of automation goals.
• Apply critical thinking and problem-solving skills to address complex business challenges.
• Utilize negotiation skills to balance business priorities, technical feasibility, and resource constraints.
• Stay updated on the latest AI, ML, and automation trends to drive innovation and efficiency.

Key requirements

• 10+ years of overall IT experience, including at least 4 years delivering AI solutions.
• Proven experience in Business Process Automation/Digital Process Automation.
• Strong technical expertise in Python; LLM architecture (transformers, embeddings, context windows); prompt engineering; LangChain/LangGraph or equivalents (LlamaIndex, CrewAI); RAG and vector databases (Pinecone/Qdrant/Chroma/pgvector/OpenSearch); agent and tool-calling frameworks, including MCP; evaluation frameworks (Ragas); LLMOps and tracing (Langfuse/Arize); and cloud AI services (Bedrock/Vertex/Azure OpenAI).
• Strong understanding of how AI technologies and generative AI can help solve business challenges, with the ability to provide strategic direction to the team.
• Experience in stakeholder management, working with cross-functional teams, and aligning automation initiatives with business goals.
• Strong collaboration skills to ensure automation solutions are effectively integrated into the BU's product suite of applications.
• Strong problem-solving, negotiation, and critical thinking abilities.
• Ability to manage multiple priorities and drive results in a fast-paced environment.