TechLead / Solutions Architect (Python & GenAI)

What You’ll Do:

• 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

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 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

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

Originally posted on Himalayas