Note: The job is a remote job and is open to candidates in USA. CrestPoint Strategic Advisors is seeking an experienced AI Engineer to join its engineering team and contribute to production AI applications. The role focuses on building full-stack AI systems, including backend agent orchestration, AI integrations, and user-facing interfaces, while collaborating with product and engineering teams to deliver reliable software quickly.
Responsibilities
- Design, develop, and deploy production AI applications and agentic systems
- Build robust backend services in Python
- Develop and integrate AI agents using modern LLM frameworks and APIs
- Work closely with product and engineering to ship new capabilities fast
- Use AI coding assistants to boost velocity without sacrificing code quality
- Write maintainable, tested, production-ready software
Skills
- Production Python development - a demonstrable track record building and deploying real systems, not just scripts
- Strong grounding in software engineering best practices: testing, deployment, maintainability
- Hands-on agentic AI experience - you've built production AI agents with frameworks like LangChain, or directly against the OpenAI or Anthropic APIs; the specific tool matters less than a real understanding of how agentic systems are designed, orchestrated, and deployed
- Experience using AI coding agents (e.g. Claude, Codex) in a professional workflow, with a clear-eyed sense of both the upside and the limits, including validation and quality control
- String demonstrated hands-on Python coding experience
- Engineers who:
- • Can hit the ground running with minimal onboarding
- • Have a real track record of shipping production software
- • Are pragmatic problem-solvers, not framework specialists
- • Enjoy building AI products end to end
- • Write clean, well-tested, maintainable code
- • Thrive in a fast-moving engineering environment
- • SQL and relational database design
- • AWS or another major cloud platform (Azure, GCP)
- • React and modern frontend development
- • Experience delivering full-stack AI applications end to end
- • REST APIs, CI/CD, containerized deployments (Docker)
- • RAG (Retrieval-Augmented Generation)
- • Vector databases
- • Prompt engineering and evaluation frameworks
- • AI observability and monitoring
- • Model evaluation and guardrails
- • MCP (Model Context Protocol)
Benefits
- Remote / Hybrid (as required)
Company Overview