FDE AI/Solutions Architect, AI, Python, Data

🔥 14 hours ago

🌐 North Macedonia, Montenegro, +5 more countries – Remote

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⏰ Full Time

🟠 Senior

🔴 Lead

💻 Solutions Engineer

👻 Ghost score 10%

What it means: the chance that no one is really hiring for this job.How to read it: 60% or higher means we think this is a ghost. Lower scores are less of a worry.How we score it: age, reposts, open roles vs team size, how fast jobs close, and whether pay is listed.Fine print: an estimate from public data, not a judgment of the company. Real jobs can score high, so treat it as a hint, not a fact.

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Provectus

WebsiteLinkedInAll Job Openings

501 - 1000 employees

Founded 2012

💼 Consulting

🏥 Healthcare

🏭 Manufacturing

Consulting • Healthcare • Manufacturing

Provectus is an artificial intelligence consultancy and solutions provider that helps businesses transform through AI. Offering both a use case and a platform approach, Provectus integrates AI into organizations to achieve unique business objectives and technical capabilities. Their solutions are cloud-native, vendor-agnostic, and open, allowing for deployment in customer's cloud without restrictive licenses. With applications in industries like retail, manufacturing, and healthcare, Provectus delivers AI-powered use cases and turnkey solutions to drive innovation and efficiency. They also offer consulting, customization, and managed AI services.

📋 Description

• Sit with the client and Forward Deployed Executive at engagement start to learn and redesign the function from first principles • Reach working fluency in domains such as insurance underwriting, healthcare revenue cycle, and asset flow • Design and ship production GenAI systems in customer environments • Implement and optimize production RAG systems • Build evaluation harnesses, define success criteria, instrument systems, and use evaluations to drive design • Write production code across AI, backend services, and data pipelines • Deploy systems to production on AWS, or GCP/Azure when required, using containers, CI/CD, automated testing, monitoring, and maintainable handover • Start from existing blueprints and feed field learnings back into them • Lead architecture reviews, produce technical design documents, contribute to standards, mentor engineers, and share knowledge • Partner with an FDX accountable for Business Unit KPIs and align technical work to outcomes • Own technical direction for proposals and scoping • Drive adoption and change management • Present outcomes credibly to customer engineers and executives • Shape commitments before they are finalized

🎯 Requirements

• B2+ English • Proactive and self-directed; able to identify problems before they are handed to you • Comfortable with ambiguity and ownership • Willing to understand and perform the client's work before coding • Credible with senior stakeholders, including BU heads and CTOs • Able to produce scoped, phased delivery plans with deliverables, dependencies, risks, and cost estimates • 7+ years building and running production systems • Solid AI/ML foundations and ability to reason about model failure modes • Experience designing and shipping production LLM applications and agentic workflows • Experience with multi-step workflows, graph-based orchestration, tool use, state management, and partial-failure recovery • Experience with LLM APIs such as Anthropic, AWS Bedrock, or OpenAI and agent frameworks • Experience building and optimizing production RAG systems • Strong engineering fundamentals; proficiency in Python and/or TypeScript • Experience making and defending architectural trade-off decisions • Hands-on AWS production depth, including Bedrock, Bedrock AgentCore, Lambda, ECS, S3, SQS, ECR, or similar • Cloud-native delivery experience with containers, ECS or Kubernetes, IaC, and CI/CD applied to AI pipelines • Built or owned an evaluation suite for a non-deterministic system, including ground truth and release gates • Experience with model and agent monitoring and drift detection • Cost and latency discipline, including model tiering and caching • Hands-on production experience with the Claude ecosystem, including Claude Code, CLAUDE.md, hooks, and skills files • MCP knowledge, including why an agent may prefer it to REST integration • B2B collaboration suitability

🏖️ Benefits

• Remote-friendly culture • Internal training programs with full support for Claude, AWS, and other professional certifications • Conference attendance • Career growth and active engineer development • Access to the latest AI tools and premium subscriptions • Long-term B2B collaboration • Private medical insurance or a budget for medical needs • Paid sick leave, vacation, and public holidays • Equipment and all the tech needed for comfortable, productive work

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