Solutions Architect (AI, Python/Data)

Provectus; United States; Remote; USD 180,000 - 240,000; Full time

Benefits offered by this job

Remote with flexible hours

Professional training & certifications

Career growth path

Access to premium AI tools

Equipment provided

Job summary

Provectus is seeking a senior AI/ML engineer to design and deploy cloud-native data, LLM-based, and agentic AI solutions addressing real client challenges. You will implement and optimize RAG systems, own the technical direction from discovery to delivery, and mentor engineers across the team.

You will write production-grade Python for AI integrations and RESTful APIs, build ETL/ELT workflows, and deploy ML models in production with CI/CD, monitoring, and observability.

Qualifications

• 7+ years building and running production systems beyond demos and POCs.
• Hands-on experience with production LLM-based applications and agentic workflows.
• Experience integrating AI/ML components into end-to-end solutions.
• Experience with LLM APIs (OpenAI, Anthropic, AWS Bedrock).
• Proven ability to design and optimize RAG systems for production use.
• Strong Python skills: OOP, design patterns, clean architecture, performance.
• Experience building RESTful APIs with FastAPI, Django REST, or Flask.
• Familiarity with Docker, Kubernetes, and CI/CD for ML pipelines.
• AWS (Bedrock AgentCore, Bedrock, Lambda, ECS, S3, SQS, ECR) or GCP familiarity.
• Ability to perform architectural trade-off decisions and lead reviews.

Responsibilities

• Design and build cloud-native data, LLM-based, and agentic AI solutions addressing client challenges.
• Implement and optimize RAG systems for production use cases.
• Build and maintain relationships with customer stakeholders as a technical advisor.
• Support presales: discovery calls, proposals, scoping, client demos.
• Own technical direction from discovery to delivery as go-to authority.
• Write production-grade Python across AI integrations, backend services, and RESTful APIs.
• Build ETL/ELT workflows with modern orchestration and distributed tooling.
• Deploy ML and LLM-based solutions and implement MLOps practices.
• Lead architecture reviews, produce design documents, and contribute to standards.
• Mentor engineers, conduct code reviews, and share knowledge across the team.

Skills

Full-stack mindset

AI tooling usage

Proactive and self-directed

B2+ English

Tools

Claude Code

Copilot

OpenAI API

Anthropic API

AWS Bedrock

Docker

Kubernetes

FastAPI

Django REST

Job description

What You’ll Do:

• Design and build cloud-native data, LLM-based, and agentic AI solutions addressing real client business challenges

• Implement and optimize RAG systems for production use cases

• Build and maintain strong relationships with key customer stakeholders, acting as a trusted technical advisor.

• Support presales: discovery calls, technical proposals, scoping, and client-facing demos

• Own the technical direction of client engagements from discovery through delivery — the go-to authority for clients and the internal team

• Write clean, production-grade Python across AI integrations, backend services, and RESTful APIs

• Build and maintain ETL/ELT workflows using modern orchestration and distributed computing tools.

• Deploy ML and LLM-based solutions

• Implement MLOps, LLMOps, and AgentOps practices: CI/CD, automated testing, model monitoring, and experiment tracking.

• Lead architecture reviews, produce technical design documents, and contribute to standards

• Mentor engineers, lead code reviews, and share knowledge across the team.

What You’ll Bring:

Mindset

• Full-stack mindset, comfortable across AI, backend development, and cloud infrastructure
• Already using AI tools in your daily workflow (Claude Code, Copilot, or similar)
• Proactive and self-directed; you own outcomes end-to-end and spot problems before they’re handed to you
• B2+ English, comfortable collaborating across distributed, multicultural teams

Presales & Client Engagement

• Owns the client technical relationship; leading discovery, decomposing ambiguous requirements into technicalcomponents, presenting architecture, and pushing back on scope when it doesn’t match timeline or budget
• Produces scoped, phased delivery plans with clear deliverables, dependencies, and risks
• Experience with cost estimation and cloud architecture cost optimization

AI & Python/ Data & Cloud

• 7+ years building and running production systems — not only demos and POCs
• Hands-on experience building production LLM-based applications and agentic workflows
• Experience in integrating AI/ML components into solutions
• Experience with LLM APIs (OpenAI, Anthropic, or AWS Bedrock)
• Experience building and optimizing RAG systems
• Understanding of LLM evaluation techniques and quality assurance approaches
• Experience deploying and maintaining AI/ML models in production environments
• Python skills: OOP, design patterns, clean architecture, and performance optimization
• Experience building RESTful APIs with FastAPI, Django REST, or Flask
• Experience in making and defending architectural trade-off decisions
• Experience with Docker and Kubernetes
• Hands-on experience with AWS (Bedrock AgentCore, Bedrock, Lambda, ECS, S3, SQS, ECR, or similar); GCP considered
• Understanding of CI/CD practices applied to ML and AI pipelines
• Familiarity with model monitoring, observability, and drift detection_._

Nice to Have

• AWS and Claude Code Certifications
• CI/CD pipeline experience (GitHub Actions, GitLab CI)
• Experience in an additional language (Go, Node.js, or Rust).
• Hands-on experience with Apache Spark, Apache Airflow, Kafkа

What We Offer:

• Opportunity to work with cutting-edge AI and cloud solutions
• Internal training programs (Leadership, Public Speaking, and more) with full support for AWS and other professional certifications
• Career growth: a clear path toward SA or beyond; we actively develop our engineers
• Access to the latest AI tools and premium subscriptions
• Long-term B2B collaboration
• Remote with flexible hours
• Private medical insurance or a budget for your medical needs
• Paid sick leave, vacation, and public holidays
• Equipment and all the tech you need for comfortable, productive work