AI Engagement Lead

Jobtailor; Deutschland; Remote; EUR 110.000 - 160.000; Vollzeit

Zusammenfassung

Jobtailor is seeking a senior AI/GenAI Delivery Lead to drive engagements from discovery through production. You will act as the primary technical and delivery interface for clients and senior stakeholders, translating business objectives into AI/ML solution requirements.

You will own project planning, coordinate across AI Engineers, Data Scientists, Data Engineers, Product Managers, and client teams, and lead hands-on development of LLM-powered applications, RAG systems, and agent workflows in

Qualifikationen

• 10+ years in software engineering or AI/ML related fields.
• Hands-on experience building and deploying AI/ML or Generative AI solutions.
• Proven leadership of technical teams or AI pods while staying hands-on.
• Strong Python proficiency and production-grade app development.
• Deep understanding of LLMs, Generative AI, NLP, RAG, and AI agents.
• Experience with multiple AI frameworks and LLM APIs.
• Experience with vector databases and semantic search.
• Cloud-based AI solutions on AWS/Azure/GCP.
• Understanding of APIs, microservices, Docker, CI/CD, and production deployment.
• Strong client-facing communication and problem translation skills.
• Master's in Business Analytics or equivalent experience.

Aufgaben

• Lead AI/GenAI engagements from discovery to production.
• Serve as the primary technical and delivery interface for clients and senior stakeholders.
• Translate business objectives into AI/ML solution requirements and actionable plans.
• Own project planning, timelines, milestones, risks, and dependencies.
• Coordinate across AI Engineers, Data Scientists, Data Engineers, PMs, and client teams.
• Conduct regular client discussions, status reviews, and solutioning sessions.
• Identify delivery risks and drive resolution.
• Architect, develop, and deploy AI/ML and GenAI solutions for enterprise use cases.
• Lead hands-on development of LLM-powered apps, RAG systems, agents, and workflows.
• Design end-to-end AI architectures including LLM integration, prompts, embeddings, tool calling, and monitoring.
• Work with LangChain, LangGraph, LlamaIndex, Semantic Kernel, or equivalents.
• Integrate foundation models like OpenAI, Azure OpenAI, Anthropic, Bedrock, Gemini, or open-source models.
• Develop production-grade AI services and APIs using Python, FastAPI, Docker, Kubernetes, and cloud platforms.
• Design retrieval pipelines with document processing, embedding generation, and vector search.

Kenntnisse

Python Programming

LLM Integration

LangChain

LangGraph

LlamaIndex

Semantic Kernel

Docker

Kubernetes

Cloud Platforms

APIs & Microservices

AI/GenAI Frameworks

Stakeholder Management

Ausbildung

Master's in Business Analytics

Tools

LangChain

LangGraph

LlamaIndex

Semantic Kernel

OpenAI

Azure OpenAI

Anthropic Claude

Amazon Bedrock

Gemini

FastAPI

Jobbeschreibung

• Lead AI/GenAI engagements from discovery and solution definition through development, deployment, and production
• Serve as the primary technical and delivery interface for clients and senior stakeholders
• Translate business objectives into AI/ML solution requirements and actionable engineering plans
• Own project planning, prioritization, timelines, milestones, risks, dependencies, and overall delivery
• Coordinate across AI Engineers, Data Scientists, Data Engineers, Product Managers, and client teams
• Conduct regular client discussions, status reviews, technical walkthroughs, and solutioning sessions
• Identify delivery risks, technical challenges, resource constraints, and dependencies and drive them toward resolution
• Architect, develop, and deploy AI/ML and Generative AI solutions for enterprise use cases
• Lead hands-on development of LLM-powered applications, RAG systems, AI agents, and agentic workflows
• Design and implement end-to-end AI application architectures, including LLM integration, prompt engineering, RAG pipelines, embeddings and vector databases, tool/function calling, agent orchestration, evaluation, and monitoring
• Work with frameworks such as LangChain, LangGraph, LlamaIndex, Semantic Kernel, or equivalent technologies
• Integrate foundation models and LLM platforms such as OpenAI, Azure OpenAI, Anthropic Claude, Amazon Bedrock, Gemini, or open-source models
• Develop production-grade AI services and APIs using Python, FastAPI, Docker, Kubernetes, and cloud platforms
• Design retrieval pipelines including document processing, chunking, embedding generation, vector search, hybrid retrieval, and re-ranking

Requirements

• 10+ years of experience in software engineering, AI/ML engineering, data science, or a related technical field
• Strong hands-on experience building and deploying AI/ML or Generative AI solutions
• Proven experience leading technical teams or AI engineering pods while remaining hands-on
• Strong proficiency in Python and experience developing production-grade applications
• Strong understanding of LLMs, Generative AI, NLP, RAG, and AI agents
• Experience with one or more AI/GenAI frameworks such as LangChain, LangGraph, LlamaIndex, Semantic Kernel, or equivalent
• Experience working with LLM APIs/foundation models such as OpenAI, Azure OpenAI, Anthropic, Bedrock, Gemini, or open-source LLMs
• Experience with vector databases and semantic search
• Experience designing and deploying cloud-based AI solutions on AWS, Azure, or GCP
• Strong understanding of APIs, microservices, Docker, CI/CD, and production deployment
• Experience with AI evaluation, monitoring guardrails, and responsible AI is highly desirable
• Strong client-facing communication and stakeholder management skills
• Demonstrated ability to translate ambiguous business problems into practical technical solutions
• Master's in Business Analytics or equivalent work experience

Core Competencies

Demonstrates expertise in leading AI/ML engagements, translating business objectives into actionable engineering plans, and architecting end-to-end AI solutions. Proficient in developing production-grade applications using Python and integrating various AI frameworks and LLM platforms.

Highest-signal resume keywords

• AI/ML Solution Development
• Python Programming
• LLM Integration
• Cloud-Based AI Solutions
• Client-Facing Communication

ATS Optimization Keywords

Hard Skills

• AI/ML Engineering
• Generative AI Solutions
• Production-Grade Application Development
• Vector Databases
• NLP
• RAG Systems
• API Development\
• Microservices
• Docker
• CI/CD

Soft Skills

• Stakeholder Management
• Technical Leadership
• Problem Solving
• Communication

Certifications & Qualifications

• Master's in Business Analytics

Industry Keywords

• AI Solutions
• Machine Learning
• Data Science
• Cloud Platforms
• Enterprise Use Cases

Tools & Technologies

• LangChain
• LangGraph
• LlamaIndex
• Semantic Kernel
• OpenAI
• Azure OpenAI
• Anthropic Claude
• Amazon Bedrock
• Gemini
• FastAPI