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