Senior AI Engineer

About All. Cloud All. Cloud is a leader in amplifying organizations’ cloud potential through AI. With a track record of hundreds of successful migrations and implementations across AWS and Salesforce, All. Cloud has developed strategies and solutions that enable businesses of all sizes to remain at the forefront of innovation.

All. Cloud is a leader in AI-led professional and managed services. As an AWS Premier and audited managed services Partner, and Salesforce Consulting partner, All. Cloud provides comprehensive AI-led cloud journey support, from initial migration to ongoing management through our Engage Managed Services. Our expertise ensures that clients remain aligned with ecosystem best practices while focusing on their core business growth.

All. Cloud serves clients across the globe with offices in EMEA and North America. www.allcloud.io Job Summary The AI Transformation Team partners with enterprise customers to design, build, and operationalize agentic AI solutions on AWS. As an AI Engineer, you will work directly with clients across financial services, healthcare, and industrial sectors, translating complex business challenges into scalable, production-grade AI systems.

This role combines hands-on engineering with customer engagement, solution architecture, and delivery leadership. You will leverage modern AI platforms and AWS-native services to drive measurable business outcomes.

Key Responsibilities

Design, build, and deploy production-grade AI systems leveraging LLMs and agentic architectures Translate business requirements into scalable AI solution architectures and implementation roadmaps Lead and participate in discovery workshops, architecture reviews, and solution design sessions with customers Develop and optimize agentic workflows, including tool integration, multi-agent orchestration, and human-in-the-loop processes Integrate AI solutions with enterprise platforms (e.

g., Slack, Salesforce, Service. Now, Jira) Implement secure, scalable cloud architectures on AWS, following best practices for multi-account and multi-tenant environments Build and maintain CI/CD pipelines, infrastructure as code, and observability frameworks Collaborate cross-functionally with engineering, data, and business stakeholders to ensure successful delivery Scope, estimate, and deliver AI and cloud projects end-to-end Create key technical deliverables, including solution architecture documents, SOWs, runbooks, and handover documentation Present technical solutions and recommendations to both engineering teams and executive stakeholders (CTO, CIO, CDO) Requirements Skills & Qualifications 6+ years of production-grade software engineering experience (Python and/or TypeScript preferred) 3+ years in applied AI/LLMs, strong hands-on experience with Python, CI/CD, tool-calling, API agents, and related infrastructure skills.

Proficiency in AI-assisted development tools (Kiro, Cursor, Claude Code) Strong understanding of distributed systems, event-driven architectures, and API design Experience with serverless architectures (AWS Lambda, SQS, SNS, Step Functions, Event. Bridge) Proficiency with Infrastructure as Code (Terraform and/or AWS CDK) Experience with CI/CD pipelines, containerized workloads (ECS/EKS), and observability tooling Hands-on experience building LLM-powered applications (prompt engineering, RAG, function calling, agentic workflows) Familiarity with AWS AI/ML services (Bedrock, Sage.

Maker; Agent. Core is a plus) Understanding of agent orchestration patterns: tool usage, multi-agent coordination, human-in-the-loop workflows, and stateful conversations Experience with agent frameworks (Lang. Chain, Lang. Graph, CrewAI, Strands, or similar) Knowledge of embeddings, vector databases, and retrieval strategies Strong understanding of AWS architecture and security best practices Experience designing multi-account and multi-tenant environments Knowledge of IAM, SCPs, VPC endpoint policies, and data perimeter controls Familiarity with AWS data services (S3, DynamoDB, RDS, Kinesis, Glue, etc.)

AWS certifications (Solutions Architect, ML Specialty) are a plus Experience integrating AI into enterprise platforms (Slack, Salesforce, Service. Now, Jira, etc.) Familiarity with real-time communication protocols (SSE, Web. Sockets) Exposure to agent/UI frameworks (Vercel AI SDK, Copilot. Kit, AG-UI) Understanding of API gateway patterns, authentication flows, and audit/logging requirements Experience in customer-facing roles (workshops, architecture reviews, solution design) Ability to translate business problems into technical solutions Experience scoping, estimating, and delivering projects end-to-end Strong presentation skills for both technical and executive audiences Experience creating technical documentation and delivery artifacts Signs you may be a great fit Impact: Play a pivotal role in shaping a rapidly growing venture studio.

Culture: Thrive in a collaborative, innovative environment that values creativity and ownership. Growth: Access professional development opportunities and mentorship.

Benefits

Competitive salary, health/wellness packages, and flexible work options.