Provectus is a global AI and cloud consulting company helping enterprises turn artificial intelligence and data into production-ready business solutions. We specialize in designing, building, and scaling end-to-end AI/ML systems, data platforms, and cloud-native architectures, with strong expertise in AWS, MLOps, and enterprise-grade AI delivery.
We are an official Anthropic partner, working with cutting-edge foundation models to help organizations safely and effectively adopt advanced AI capabilities.
Our consulting teams operate across industries such as finance, healthcare, retail, and technology, delivering solutions with measurable business impact through hands-on engineering and advisory.
As a Technical Lead, you will drive the development of GenAI-powered solutions, including AI agents, RAG systems, and Python services. You will provide technical leadership, own solution architecture, mentor engineers, and guide projects from discovery to production.
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 technical components, 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
Python, AI & Cloud
7+ years building and running production systems not only demos and POCs
Strong understanding of AI/ML concepts and experience integrating AI/ML components into solutions
Strong Python proficiency: OOP, design patterns, clean architecture, and performance optimization
Experience building RESTful APIs with FastAPI, Django REST, or Flask
Experience making and defending architectural trade-off decisions: microservices vs monolith, sync vs event-driven, SQL vs NoSQL
Strong testing practices: pytest, mocking, and integration tests for AI systems
Experience with Docker and Kubernetes
Hands-on experience building production LLM-based applications and agentic workflows
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
Hands-on experience with AWS (SageMaker, Bedrock, Lambda, ECS, S3, SQS, ECR, or similar); GCP considered
Experience with React/Vue
AWS and Claude Code Certifications
Nice to Have
Experience with Streamlit or Gradio for AI prototyping
Modern Python tooling (ruff, uv, pyproject.toml, pyright)
CI/CD pipeline experience (GitHub Actions, GitLab CI)
Experience in an additional language (Go, Node.js, or Rust)
Front-end experience
Write clean, production-grade Python across AI integrations, backend services, and RESTful APIs
Implement and optimize RAG systems for production use cases
Design and build LLM-based and agentic AI solutions that address real client business challenges
Own the technical direction of client engagements from discovery through delivery
Support presales: discovery calls, technical proposals, scoping, and client-facing demos
Lead architecture reviews, produce technical design documents, and contribute to standards across the Python practice
Mentor engineers, lead code reviews, and share knowledge across the team
Build and maintain strong relationships with key client stakeholders as a trusted technical advisor
