Senior AI Solutions Architect, AWS

Jobtailor; Deutschland; Vor Ort; EUR 120.000 - 180.000; Vollzeit

Zusammenfassung

Jobtailor in Germany seeks a senior ML leader to drive technical discovery, design scalable ML architectures, and craft proposals for enterprise clients. You will present ML solutions, guide pre-sales, and lead agentic systems design across RAG, LLMs, and tool ecosystems. A strong background in MLOps and AWS services is essential.

You will mentor engineers, coordinate with delivery teams, and shape reusable patterns and reference architectures for client engagements.

Qualifikationen

• 6–8+ years of experience in ML or data science roles.
• Proven track record in client-facing technical roles, including pre-sales or discovery.
• Portfolio of architected ML solutions delivering business impact.
• Deep understanding of the ML lifecycle from data ingestion to production.
• Experience designing scalable, production-grade ML architectures across domains (RAG, CV, time series, RS).
• Strong experience with LLM-based applications and agentic systems.
• Proficiency with agent design patterns, state management and orchestration frameworks (LangGraph, LangChain).
• Hands-on experience with Claude ecosystem (Claude Code, Claude Agent SDK).
• Knowledge of MCP architecture for client integrations.
• Experience with AI-assisted development tools (Cursor, GitHub Copilot).
• AWS ML/data services including SageMaker, Bedrock, Lambda, ECS.
• Knowledge of serverless architectures for agentic workflows.
• Familiarity with MLOps, LLMOps, AgentOps practices.

Aufgaben

• Lead technical discovery sessions with prospective clients and translate problems into ML solutions.
• Design end-to-end ML architectures and write proposals with scope, timeline, and cost.
• Deliver technical presentations to both technical and non-technical audiences.
• Serve as primary technical contact and manage stakeholder expectations.
• Mentor engineers on client communication and solution design.
• Develop reference architectures for agentic patterns and POC demos.

Kenntnisse

Client-facing leadership

ML lifecycle design

Agentic systems design

LLM-based applications

Pre-sales / discovery

MLOps / AgentOps

Cloud: AWS ML

Production ML architectures

Ausbildung

Bachelor's degree in Computer Science

Master's degree in Data Science

Master's degree in Engineering

Tools

LangGraph

LangChain agents

Claude ecosystem

MCP architecture

Cursor

GitHub Copilot

Claude Code

SageMaker

Bedrock

Lambda

ECS

API Gateway

Step Functions

Jobbeschreibung

• Lead technical discovery sessions with prospective clients to understand business problems and translate them into feasible ML solutions
• Design end-to-end ML architectures and author technical proposals, including scope, timeline, cost, and resource estimates
• Create and deliver compelling technical presentations and demonstrations to both technical and non-technical audiences
• Support General Managers in winning new business through technical leadership
• Architect agentic AI solutions leveraging autonomous decision‑making, tool orchestration, and LLM‑based workflows
• Design MCP (Model Context Protocol) integration strategies for client environments
• Evaluate and recommend appropriate agent frameworks (LangGraph, Claude Agent SDK, and others) based on client use cases
• Develop reference architectures for common agentic patterns including RAG agents, multi‑agent systems, and tool‑using agents
• Build POC demonstrations showcasing agentic capabilities using AI‑assisted development tools
• Advise clients on build‑vs‑buy decisions for agentic components and assess AgentOps requirements including monitoring, evaluation, and cost optimization
• Serve as the primary technical point of contact throughout the project lifecycle
• Manage technical stakeholder expectations and navigate complex organizational dynamics
• Build long‑term trusted advisor relationships with clients
• Collaborate with delivery teams to ensure smooth project handoffs
• Provide technical guidance during project execution
• Contribute to reusable solution patterns, agentic accelerators, and Provectus AI toolkit documentation
• Mentor engineers on client communication and solution design

Requirements

• 6–8+ years of demonstrated experience in ML or data science roles
• Proven track record in client‑facing technical roles, including leading pre‑sales or discovery engagements
• Portfolio of successfully architected and delivered ML solutions with a history of winning business through technical leadership
• Deep understanding of the full ML lifecycle from data ingestion through production deployment
• Experience designing scalable, production‑grade ML architectures across multiple ML domains (RAG, Computer Vision, Time Series, Recommendation Systems, and others)
• Strong experience architecting LLM‑based applications, including agentic systems
• Proficiency with agent design patterns, state management, and orchestration frameworks (LangGraph, LangChain agents, multi‑agent systems)
• Hands‑on experience with the Claude ecosystem: Claude Code, Claude Agent SDK, and Anthropic's tool ecosystem
• Working knowledge of Model Context Protocol (MCP) architecture for designing client integrations
• Demonstrated use of AI‑assisted development tools (Cursor, GitHub Copilot, Claude Code) for rapid prototyping and POC development
• Advanced knowledge of AWS ML and data services including SageMaker, Bedrock, Lambda, and ECS
• Deep understanding of Amazon Bedrock agents, knowledge bases, and model hosting options
• Experience with serverless architectures (Lambda, API Gateway, Step Functions) for agentic workflows
• Knowledge of MLOps, LLMOps, and AgentOps practices including monitoring, evaluation, and cost optimization
• Ability to design cost‑effective solutions with clear TCO analysis and trade‑off assessment
• Understanding of data security, privacy, and compliance requirements
• Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or a related technical field, or equivalent experience with a demonstrable technical foundation

Certifications & Qualifications

• Bachelor's degree in Computer Science
• Master's degree in Data Science
• Master's degree in Engineering