Please send your resume at anila.dada@amyantek.com if you are interested in this role.If you are not interested, please feel free to pass it in your network for anyone looking for work.
Senior AI Engineer – Production AI / LLM Applications
We are looking for a Senior AI Engineer to design, build, and deploy production-ready AI applications and AI agents for enterprise clients.
This role requires someone who combines strong AI/LLM expertise with real software engineering experience. You should be comfortable taking an AI use case from concept or prototype through architecture, development, testing, deployment, monitoring, and production support.
You may work with tools such as Claude, GitHub Copilot, OpenAI Codex, and enterprise data platforms such as Databricks to develop AI agents and applications for specific business processes and use cases.
Important: We are not looking for someone whose experience is primarily prompt engineering, prototypes, or "vibe coding." We need an engineer who understands how to turn AI prototypes into secure, reliable, maintainable, production-grade software.
What You’ll Do
- Design and build production-grade AI applications and services using Python
- Translate business requirements and AI use cases into practical technical solutions
- Build AI agents, backend services, APIs, workflows, and integrations
- Integrate LLMs and AI capabilities with enterprise applications and data platforms
- Design evaluation frameworks and test cases to measure AI accuracy, quality, reliability, and consistency
- Develop approaches to make probabilistic LLM-based systems more predictable and dependable
- Implement observability, logging, tracing, instrumentation, and monitoring
- Build reusable components for prompting, model interaction, evaluation, retrieval, and orchestration
- Develop automated testing and CI/CD pipelines
- Deploy and support AI applications in production environments
- Troubleshoot production issues and improve application performance and reliability
- Contribute to architecture and technology decisions
- Establish engineering best practices for Python and AI application development
- Work directly with clients and stakeholders to refine requirements and evaluate technical trade-offs
Must-Have Experience
- 5+ years of software engineering, backend engineering, applied AI, or related experience
- Strong Python development skills
- Experience building maintainable, production-grade Python applications
- Proven experience taking AI/LLM applications beyond POC/prototype into production
- Experience building backend services and APIs using Python
- Strong software engineering fundamentals: modular architecture, testing, Git/version control, and CI/CD
- Hands-on experience evaluating LLM outputs and creating repeatable AI test cases
- Experience with production observability, logging, tracing, instrumentation, and monitoring
- Understanding of the challenges involved in making probabilistic AI systems reliable
- Experience integrating applications with APIs, enterprise data sources, and business systems
- Strong problem-solving skills and ability to work beyond predefined frameworks
- Strong client-facing and stakeholder communication skills
- Ability to combine hands-on engineering with technical architecture and solution design
Nice-to-Haves
- RAG, semantic search, embeddings, and vector databases
- Agentic AI and multi-step LLM workflows
- Structured LLM outputs, function/tool calling, and schema-driven AI applications
- AI evaluation, experimentation, and observability platforms
- Databricks
- Microsoft Azure AI Foundry / Microsoft Fabric
- Cloud infrastructure and containerization
- Production deployment of Python services
- Modern Python API, validation, testing, and dependency-management frameworks
- Enterprise data platforms and semantic layers
- Experience with Claude, GitHub Copilot, OpenAI Codex, or similar AI development tools
- Consulting, financial services, manufacturing, or other enterprise experience
- Experience supporting business-critical or external client-facing production applications
Ideal Candidate
You are not simply someone who can build an impressive AI demo. You understand software architecture, production deployment, testing, reliability, monitoring, security, and maintainability and can turn an AI concept into an enterprise-ready solution.
